Overview

Dataset statistics

Number of variables35
Number of observations569501
Missing cells10462746
Missing cells (%)52.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 GiB
Average record size in memory2.0 KiB

Variable types

CAT29
NUM6

Warnings

RECVDATE has a high cardinality: 260 distinct values High cardinality
STATE has a high cardinality: 64 distinct values High cardinality
RPT_DATE has a high cardinality: 109 distinct values High cardinality
SYMPTOM_TEXT has a high cardinality: 544604 distinct values High cardinality
DATEDIED has a high cardinality: 297 distinct values High cardinality
VAX_DATE has a high cardinality: 1701 distinct values High cardinality
ONSET_DATE has a high cardinality: 1126 distinct values High cardinality
LAB_DATA has a high cardinality: 125645 distinct values High cardinality
OTHER_MEDS has a high cardinality: 218020 distinct values High cardinality
CUR_ILL has a high cardinality: 51645 distinct values High cardinality
HISTORY has a high cardinality: 146407 distinct values High cardinality
PRIOR_VAX has a high cardinality: 23877 distinct values High cardinality
SPLTTYPE has a high cardinality: 77868 distinct values High cardinality
TODAYS_DATE has a high cardinality: 367 distinct values High cardinality
ALLERGIES has a high cardinality: 99925 distinct values High cardinality
CAGE_YR is highly correlated with AGE_YRSHigh correlation
AGE_YRS is highly correlated with CAGE_YRHigh correlation
STATE has 69104 (12.1%) missing values Missing
AGE_YRS has 58342 (10.2%) missing values Missing
CAGE_YR has 110446 (19.4%) missing values Missing
CAGE_MO has 567757 (99.7%) missing values Missing
RPT_DATE has 569151 (99.9%) missing values Missing
DIED has 562319 (98.7%) missing values Missing
DATEDIED has 563051 (98.9%) missing values Missing
L_THREAT has 560732 (98.5%) missing values Missing
ER_VISIT has 569449 (> 99.9%) missing values Missing
HOSPITAL has 536233 (94.2%) missing values Missing
HOSPDAYS has 546713 (96.0%) missing values Missing
X_STAY has 569195 (99.9%) missing values Missing
DISABLE has 560782 (98.5%) missing values Missing
RECOVD has 49549 (8.7%) missing values Missing
VAX_DATE has 39266 (6.9%) missing values Missing
ONSET_DATE has 44284 (7.8%) missing values Missing
NUMDAYS has 66139 (11.6%) missing values Missing
LAB_DATA has 346365 (60.8%) missing values Missing
V_FUNDBY has 569108 (99.9%) missing values Missing
OTHER_MEDS has 234118 (41.1%) missing values Missing
CUR_ILL has 304713 (53.5%) missing values Missing
HISTORY has 211582 (37.2%) missing values Missing
PRIOR_VAX has 542711 (95.3%) missing values Missing
SPLTTYPE has 404977 (71.1%) missing values Missing
BIRTH_DEFECT has 569178 (99.9%) missing values Missing
OFC_VISIT has 462554 (81.2%) missing values Missing
ER_ED_VISIT has 499046 (87.6%) missing values Missing
ALLERGIES has 273103 (48.0%) missing values Missing
HOSPDAYS is highly skewed (γ1 = 106.7097018) Skewed
NUMDAYS is highly skewed (γ1 = 46.71933369) Skewed
VAERS_ID has unique values Unique
NUMDAYS has 221204 (38.8%) zeros Zeros

Reproduction

Analysis started2021-09-30 16:55:38.020739
Analysis finished2021-09-30 16:56:40.165152
Duration1 minute and 2.14 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

VAERS_ID
Real number (ℝ≥0)

UNIQUE

Distinct569501
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1281987.761
Minimum916600
Maximum1708053
Zeros0
Zeros (%)0.0%
Memory size4.3 MiB
2021-09-30T12:56:40.363940image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum916600
5-th percentile947023
Q11088223
median1258457
Q31482806
95-th percentile1652383
Maximum1708053
Range791453
Interquartile range (IQR)394583

Descriptive statistics

Standard deviation228472.5632
Coefficient of variation (CV)0.1782174293
Kurtosis-1.159440595
Mean1281987.761
Median Absolute Deviation (MAD)187949
Skewness0.1889093472
Sum7.30093312e+11
Variance5.219971213e+10
MonotocityNot monotonic
2021-09-30T12:56:40.450485image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
10526741< 0.1%
 
10555741< 0.1%
 
11047181< 0.1%
 
11026711< 0.1%
 
10596641< 0.1%
 
10637621< 0.1%
 
10514761< 0.1%
 
10494291< 0.1%
 
10760561< 0.1%
 
11620821< 0.1%
 
10740091< 0.1%
 
10801541< 0.1%
 
10781071< 0.1%
 
10719661< 0.1%
 
10699191< 0.1%
 
11579841< 0.1%
 
10985731< 0.1%
 
11006201< 0.1%
 
11067611< 0.1%
 
11088081< 0.1%
 
10862791< 0.1%
 
10883261< 0.1%
 
10821811< 0.1%
 
10842281< 0.1%
 
10944671< 0.1%
 
Other values (569476)569476> 99.9%
 
ValueCountFrequency (%) 
9166001< 0.1%
 
9166011< 0.1%
 
9166021< 0.1%
 
9166031< 0.1%
 
9166041< 0.1%
 
9166051< 0.1%
 
9166061< 0.1%
 
9166071< 0.1%
 
9166081< 0.1%
 
9166091< 0.1%
 
ValueCountFrequency (%) 
17080531< 0.1%
 
17080521< 0.1%
 
17080501< 0.1%
 
17080491< 0.1%
 
17080481< 0.1%
 
17080471< 0.1%
 
17080461< 0.1%
 
17080451< 0.1%
 
17080441< 0.1%
 
17080431< 0.1%
 

RECVDATE
Categorical

HIGH CARDINALITY

Distinct260
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.3 MiB
08/22/2021
 
14600
08/15/2021
 
12189
08/21/2021
 
10509
08/28/2021
 
9970
04/13/2021
 
5742
Other values (255)
516491 
ValueCountFrequency (%) 
08/22/2021146002.6%
 
08/15/2021121892.1%
 
08/21/2021105091.8%
 
08/28/202199701.8%
 
04/13/202157421.0%
 
08/23/202146920.8%
 
04/16/202145740.8%
 
04/14/202145480.8%
 
08/13/202141760.7%
 
04/09/202141390.7%
 
04/07/202141360.7%
 
04/15/202140190.7%
 
04/22/202139910.7%
 
04/08/202139400.7%
 
04/12/202139130.7%
 
04/23/202138070.7%
 
03/31/202137320.7%
 
04/24/202137170.7%
 
04/21/202137150.7%
 
01/08/202137150.7%
 
04/27/202136980.6%
 
08/11/202136820.6%
 
04/01/202136010.6%
 
01/28/202135850.6%
 
04/10/202135790.6%
 
Other values (235)43753276.8%
 
2021-09-30T12:56:40.549442image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-09-30T12:56:40.619998image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length10
Median length10
Mean length10
Min length10

Overview of Unicode Properties

Unique unicode characters11
Unique unicode categories2 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
2145471825.5%
 
0133878923.5%
 
/113900220.0%
 
191060016.0%
 
81655712.9%
 
41561982.7%
 
31499292.6%
 
51263692.2%
 
6945481.7%
 
7854961.5%
 
9737901.3%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number455600880.0%
 
Other Punctuation113900220.0%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
2145471831.9%
 
0133878929.4%
 
191060020.0%
 
81655713.6%
 
41561983.4%
 
31499293.3%
 
51263692.8%
 
6945482.1%
 
7854961.9%
 
9737901.6%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
/1139002100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Common5695010100.0%
 

Most frequent Common characters

ValueCountFrequency (%) 
2145471825.5%
 
0133878923.5%
 
/113900220.0%
 
191060016.0%
 
81655712.9%
 
41561982.7%
 
31499292.6%
 
51263692.2%
 
6945481.7%
 
7854961.5%
 
9737901.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII5695010100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
2145471825.5%
 
0133878923.5%
 
/113900220.0%
 
191060016.0%
 
81655712.9%
 
41561982.7%
 
31499292.6%
 
51263692.2%
 
6945481.7%
 
7854961.5%
 
9737901.3%
 

STATE
Categorical

HIGH CARDINALITY
MISSING

Distinct64
Distinct (%)< 0.1%
Missing69104
Missing (%)12.1%
Memory size4.3 MiB
CA
55566 
FL
33734 
TX
 
31950
NY
 
30836
IN
 
21752
Other values (59)
326559 
ValueCountFrequency (%) 
CA555669.8%
 
FL337345.9%
 
TX319505.6%
 
NY308365.4%
 
IN217523.8%
 
PA209703.7%
 
IL182783.2%
 
OH171013.0%
 
MI167172.9%
 
NJ160142.8%
 
NC146092.6%
 
WA133942.4%
 
VA133462.3%
 
MA131912.3%
 
GA127852.2%
 
AZ123332.2%
 
MD112782.0%
 
MN109631.9%
 
CO105301.8%
 
WI99911.8%
 
MO85841.5%
 
TN82391.4%
 
OR77131.4%
 
CT74091.3%
 
KY66851.2%
 
Other values (39)7642913.4%
 
(Missing)6910412.1%
 
2021-09-30T12:56:40.795600image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique3 ?
Unique (%)< 0.1%
2021-09-30T12:56:40.865747image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length2
Mean length2.121341315
Min length2

Overview of Unicode Properties

Unique unicode characters29
Unique unicode categories2 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
A16007613.3%
 
n13820811.4%
 
N1163109.6%
 
C953537.9%
 
I773336.4%
 
M717015.9%
 
a691055.7%
 
L613885.1%
 
T551044.6%
 
O496114.1%
 
Y382993.2%
 
F337372.8%
 
X319582.6%
 
W262872.2%
 
P230891.9%
 
H220421.8%
 
V209211.7%
 
D190181.6%
 
K180661.5%
 
J160141.3%
 
R149811.2%
 
S133921.1%
 
G128631.1%
 
Z123331.0%
 
E69920.6%
 
Other values (4)39250.3%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter100079282.8%
 
Lowercase Letter20731417.2%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
A16007616.0%
 
N11631011.6%
 
C953539.5%
 
I773337.7%
 
M717017.2%
 
L613886.1%
 
T551045.5%
 
O496115.0%
 
Y382993.8%
 
F337373.4%
 
X319583.2%
 
W262872.6%
 
P230892.3%
 
H220422.2%
 
V209212.1%
 
D190181.9%
 
K180661.8%
 
J160141.6%
 
R149811.5%
 
S133921.3%
 
G128631.3%
 
Z123331.2%
 
E69920.7%
 
U39170.4%
 
B5< 0.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n13820866.7%
 
a6910533.3%
 
x1< 0.1%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin1208106100.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
A16007613.3%
 
n13820811.4%
 
N1163109.6%
 
C953537.9%
 
I773336.4%
 
M717015.9%
 
a691055.7%
 
L613885.1%
 
T551044.6%
 
O496114.1%
 
Y382993.2%
 
F337372.8%
 
X319582.6%
 
W262872.2%
 
P230891.9%
 
H220421.8%
 
V209211.7%
 
D190181.6%
 
K180661.5%
 
J160141.3%
 
R149811.2%
 
S133921.1%
 
G128631.1%
 
Z123331.0%
 
E69920.6%
 
Other values (4)39250.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII1208106100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
A16007613.3%
 
n13820811.4%
 
N1163109.6%
 
C953537.9%
 
I773336.4%
 
M717015.9%
 
a691055.7%
 
L613885.1%
 
T551044.6%
 
O496114.1%
 
Y382993.2%
 
F337372.8%
 
X319582.6%
 
W262872.2%
 
P230891.9%
 
H220421.8%
 
V209211.7%
 
D190181.6%
 
K180661.5%
 
J160141.3%
 
R149811.2%
 
S133921.1%
 
G128631.1%
 
Z123331.0%
 
E69920.6%
 
Other values (4)39250.3%
 

AGE_YRS
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct144
Distinct (%)< 0.1%
Missing58342
Missing (%)10.2%
Infinite0
Infinite (%)0.0%
Mean49.3766859
Minimum0
Maximum119
Zeros1
Zeros (%)< 0.1%
Memory size4.3 MiB
2021-09-30T12:56:40.932381image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile18
Q135
median50
Q364
95-th percentile79
Maximum119
Range119
Interquartile range (IQR)29

Descriptive statistics

Standard deviation18.82628916
Coefficient of variation (CV)0.3812789137
Kurtosis-0.7547235061
Mean49.3766859
Median Absolute Deviation (MAD)15
Skewness0.01087300755
Sum25239337.39
Variance354.4291637
MonotocityNot monotonic
2021-09-30T12:56:41.012026image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
5097161.7%
 
6595091.7%
 
6092031.6%
 
5191691.6%
 
5891441.6%
 
5990761.6%
 
5689621.6%
 
5789111.6%
 
4089001.6%
 
6688931.6%
 
3888921.6%
 
3988631.6%
 
6187971.5%
 
3787791.5%
 
4987761.5%
 
4187631.5%
 
3686891.5%
 
6286081.5%
 
5286081.5%
 
5585911.5%
 
6385731.5%
 
4285261.5%
 
6785031.5%
 
4384931.5%
 
3584881.5%
 
Other values (119)28972750.9%
 
(Missing)5834210.2%
 
ValueCountFrequency (%) 
01< 0.1%
 
0.0845< 0.1%
 
0.17129< 0.1%
 
0.2526< 0.1%
 
0.3389< 0.1%
 
0.4223< 0.1%
 
0.566< 0.1%
 
0.5840< 0.1%
 
0.6713< 0.1%
 
0.7518< 0.1%
 
ValueCountFrequency (%) 
1193< 0.1%
 
1155< 0.1%
 
1131< 0.1%
 
1091< 0.1%
 
1062< 0.1%
 
1056< 0.1%
 
1044< 0.1%
 
10318< 0.1%
 
10224< 0.1%
 
10149< 0.1%
 

CAGE_YR
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct115
Distinct (%)< 0.1%
Missing110446
Missing (%)19.4%
Infinite0
Infinite (%)0.0%
Mean49.04191437
Minimum0
Maximum120
Zeros1344
Zeros (%)0.2%
Memory size4.3 MiB
2021-09-30T12:56:41.090216image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile18
Q134
median49
Q364
95-th percentile79
Maximum120
Range120
Interquartile range (IQR)30

Descriptive statistics

Standard deviation18.97204892
Coefficient of variation (CV)0.3868537589
Kurtosis-0.7096830573
Mean49.04191437
Median Absolute Deviation (MAD)15
Skewness0.006852441575
Sum22512936
Variance359.9386402
MonotocityNot monotonic
2021-09-30T12:56:41.172585image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
5086311.5%
 
6584151.5%
 
5181511.4%
 
6081421.4%
 
3881081.4%
 
5880971.4%
 
5980021.4%
 
5779991.4%
 
4079641.4%
 
5679631.4%
 
3979561.4%
 
3779511.4%
 
6679411.4%
 
4179391.4%
 
3678771.4%
 
6178331.4%
 
4978241.4%
 
3576851.3%
 
5576541.3%
 
5276381.3%
 
4276291.3%
 
6276221.3%
 
3476191.3%
 
6376171.3%
 
4375711.3%
 
Other values (90)26122745.9%
 
(Missing)11044619.4%
 
ValueCountFrequency (%) 
013440.2%
 
13470.1%
 
253< 0.1%
 
338< 0.1%
 
4130< 0.1%
 
554< 0.1%
 
622< 0.1%
 
738< 0.1%
 
830< 0.1%
 
938< 0.1%
 
ValueCountFrequency (%) 
12041< 0.1%
 
1197< 0.1%
 
1184< 0.1%
 
1171< 0.1%
 
1131< 0.1%
 
1122< 0.1%
 
1091< 0.1%
 
1081< 0.1%
 
1061< 0.1%
 
1057< 0.1%
 

CAGE_MO
Real number (ℝ≥0)

MISSING

Distinct11
Distinct (%)0.6%
Missing567757
Missing (%)99.7%
Infinite0
Infinite (%)0.0%
Mean0.1646788991
Minimum0
Maximum1
Zeros957
Zeros (%)0.2%
Memory size4.3 MiB
2021-09-30T12:56:41.241073image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.3
95-th percentile0.7
Maximum1
Range1
Interquartile range (IQR)0.3

Descriptive statistics

Standard deviation0.2375339698
Coefficient of variation (CV)1.442406836
Kurtosis1.644515416
Mean0.1646788991
Median Absolute Deviation (MAD)0
Skewness1.51404745
Sum287.2
Variance0.05642238679
MonotocityNot monotonic
2021-09-30T12:56:41.298008image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%) 
09570.2%
 
0.2179< 0.1%
 
0.3151< 0.1%
 
0.1128< 0.1%
 
0.5106< 0.1%
 
0.474< 0.1%
 
0.657< 0.1%
 
0.728< 0.1%
 
0.826< 0.1%
 
119< 0.1%
 
0.919< 0.1%
 
(Missing)56775799.7%
 
ValueCountFrequency (%) 
09570.2%
 
0.1128< 0.1%
 
0.2179< 0.1%
 
0.3151< 0.1%
 
0.474< 0.1%
 
0.5106< 0.1%
 
0.657< 0.1%
 
0.728< 0.1%
 
0.826< 0.1%
 
0.919< 0.1%
 
ValueCountFrequency (%) 
119< 0.1%
 
0.919< 0.1%
 
0.826< 0.1%
 
0.728< 0.1%
 
0.657< 0.1%
 
0.5106< 0.1%
 
0.474< 0.1%
 
0.3151< 0.1%
 
0.2179< 0.1%
 
0.1128< 0.1%
 

SEX
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.3 MiB
F
388350 
M
160137 
U
 
21014
ValueCountFrequency (%) 
F38835068.2%
 
M16013728.1%
 
U210143.7%
 
2021-09-30T12:56:41.360673image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-09-30T12:56:41.403280image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:41.445803image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

Overview of Unicode Properties

Unique unicode characters3
Unique unicode categories1 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
F38835068.2%
 
M16013728.1%
 
U210143.7%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter569501100.0%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
F38835068.2%
 
M16013728.1%
 
U210143.7%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin569501100.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
F38835068.2%
 
M16013728.1%
 
U210143.7%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII569501100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
F38835068.2%
 
M16013728.1%
 
U210143.7%
 

RPT_DATE
Categorical

HIGH CARDINALITY
MISSING

Distinct109
Distinct (%)31.1%
Missing569151
Missing (%)99.9%
Memory size4.3 MiB
01/08/2021
 
22
01/11/2021
 
19
01/13/2021
 
14
01/12/2021
 
14
02/04/2021
 
13
Other values (104)
268 
ValueCountFrequency (%) 
01/08/202122< 0.1%
 
01/11/202119< 0.1%
 
01/13/202114< 0.1%
 
01/12/202114< 0.1%
 
02/04/202113< 0.1%
 
01/06/202113< 0.1%
 
01/05/20219< 0.1%
 
02/08/20219< 0.1%
 
01/04/20219< 0.1%
 
12/31/20208< 0.1%
 
01/27/20218< 0.1%
 
01/07/20218< 0.1%
 
05/22/20217< 0.1%
 
01/20/20217< 0.1%
 
01/28/20217< 0.1%
 
02/10/20216< 0.1%
 
01/21/20216< 0.1%
 
12/29/20205< 0.1%
 
01/29/20215< 0.1%
 
02/01/20215< 0.1%
 
02/11/20215< 0.1%
 
12/18/20205< 0.1%
 
01/22/20214< 0.1%
 
02/18/20214< 0.1%
 
02/12/20214< 0.1%
 
Other values (84)134< 0.1%
 
(Missing)56915199.9%
 
2021-09-30T12:56:41.518798image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique52 ?
Unique (%)14.9%
2021-09-30T12:56:41.589024image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length10
Median length3
Mean length3.004302012
Min length3

Overview of Unicode Properties

Unique unicode characters13
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n113830266.5%
 
a56915133.3%
 
29260.1%
 
08580.1%
 
1705< 0.1%
 
/700< 0.1%
 
363< 0.1%
 
861< 0.1%
 
551< 0.1%
 
442< 0.1%
 
637< 0.1%
 
931< 0.1%
 
726< 0.1%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter170745399.8%
 
Decimal Number28000.2%
 
Other Punctuation700< 0.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n113830266.7%
 
a56915133.3%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
292633.1%
 
085830.6%
 
170525.2%
 
3632.2%
 
8612.2%
 
5511.8%
 
4421.5%
 
6371.3%
 
9311.1%
 
7260.9%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
/700100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin170745399.8%
 
Common35000.2%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n113830266.7%
 
a56915133.3%
 

Most frequent Common characters

ValueCountFrequency (%) 
292626.5%
 
085824.5%
 
170520.1%
 
/70020.0%
 
3631.8%
 
8611.7%
 
5511.5%
 
4421.2%
 
6371.1%
 
9310.9%
 
7260.7%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII1710953100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n113830266.5%
 
a56915133.3%
 
29260.1%
 
08580.1%
 
1705< 0.1%
 
/700< 0.1%
 
363< 0.1%
 
861< 0.1%
 
551< 0.1%
 
442< 0.1%
 
637< 0.1%
 
931< 0.1%
 
726< 0.1%
 

SYMPTOM_TEXT
Categorical

HIGH CARDINALITY

Distinct544604
Distinct (%)95.6%
Missing129
Missing (%)< 0.1%
Memory size4.3 MiB
Error: Improper Storage (temperature)
 
837
None stated.
 
773
Administered vials that were exposed to room temperature for more than 12 hours; A spontaneous report was received from an employee and a physician concerning a patient, who received Moderna's COVID-19 vaccine (mRNA-1273) and was administered with product that was exposed to room temperature for more than twelve hours. The patient's medical history was not provided. No relevant concomitant medications were reported. On 04 Jan 2021, a freezer containing a vial of mRNA-1273 failed. At 1:11 A.M. the vial experienced a temperature excursion, exceeding 8 degrees Celsius. Over time the dose thawed and reached room temperature. On 04 Jan 2021, the patient received their first of two planned doses of mRNA-1273 intramuscularly for prophylaxis of COVID-19 infection and was administered with product that was exposed to room temperature for more than twelve hours. No treatment information was provided. Action taken with mRNA-1273 in response to the event was not reported. The event, administered with product that was exposed to room temperature for more than twelve hours, was resolved on 04 Jan 2021.; Reporter's Comments: This case concerns a patient of unknown gender and age who received their first of two planned doses of mRNA-1273 (Lot unknown), reporting Product that was exposed to room temperature for more than twelve hours without any associated adverse events.
 
769
Pfizer vaccine administered after being stored at regular freezer temps longer than recommended. Dose determined invalid, client contacted and recommended repeat dose.
 
541
Vaccinated with vial that might have had a temperature excursion; Vaccinated with vial that might have had a temperature excursion; Vaccinated with vial that might have had a temperature excursion; A spontaneous report was received from a nurse concerning a patient who received Moderna's COVID-19 vaccine (mRNA-1273) and was vaccinated with vial that might have had a temperature excursion. The patient's medical history was not provided. No relevant concomitant medications were reported. On 22 Dec 2020, the nurse reported a shipment was received. The vial arrived frozen and was placed in a freezer at recommended temperature. On 02 Jan 2021, the freezer had failed, and the temperature alarm system did not alert anyone. It was noted that the freezer temperature at 5:50 AM was -5 degrees Celsius (C), at 7:50 AM the freezer was a 1.5 C. It remained between from 9.7 C at 12:51 PM then went to 8.3 C at 1:51 PM then down to -8.7 C at 2:51 PM. On 03 Jan 2021 8:45 PM, the freezer returned to its normal temperature of -20.9 C, -1 C then went to 5.5 C at 11:56 PM. On 04 Jan 2021, the temperature climbed to 19.4 C. On the same day, the patient received their first of two planned doses of mRNA-1273 (Lot number: 025J20-2A, 025L20A, or 027L20A) intramuscularly for prophylaxis of COVID-19 infection and experienced vaccination with vial that might have had a temperature excursion No treatment information was provided. Action taken with mRNA-1273 in response to the event was not reported. The outcome of the event, vaccinated with vial that might have had a temperature excursion, was considered resolved on 04 Jan 2021.; Reporter's Comments: This report refers to a case of out of specification product use, product temperature excursion issue, and product storage error for mRNA-1273. There were no reported AEs associated with this case.
 
466
Other values (544599)
565986 
ValueCountFrequency (%) 
Error: Improper Storage (temperature)8370.1%
 
None stated.7730.1%
 
Administered vials that were exposed to room temperature for more than 12 hours; A spontaneous report was received from an employee and a physician concerning a patient, who received Moderna's COVID-19 vaccine (mRNA-1273) and was administered with product that was exposed to room temperature for more than twelve hours. The patient's medical history was not provided. No relevant concomitant medications were reported. On 04 Jan 2021, a freezer containing a vial of mRNA-1273 failed. At 1:11 A.M. the vial experienced a temperature excursion, exceeding 8 degrees Celsius. Over time the dose thawed and reached room temperature. On 04 Jan 2021, the patient received their first of two planned doses of mRNA-1273 intramuscularly for prophylaxis of COVID-19 infection and was administered with product that was exposed to room temperature for more than twelve hours. No treatment information was provided. Action taken with mRNA-1273 in response to the event was not reported. The event, administered with product that was exposed to room temperature for more than twelve hours, was resolved on 04 Jan 2021.; Reporter's Comments: This case concerns a patient of unknown gender and age who received their first of two planned doses of mRNA-1273 (Lot unknown), reporting Product that was exposed to room temperature for more than twelve hours without any associated adverse events.7690.1%
 
Pfizer vaccine administered after being stored at regular freezer temps longer than recommended. Dose determined invalid, client contacted and recommended repeat dose.5410.1%
 
Vaccinated with vial that might have had a temperature excursion; Vaccinated with vial that might have had a temperature excursion; Vaccinated with vial that might have had a temperature excursion; A spontaneous report was received from a nurse concerning a patient who received Moderna's COVID-19 vaccine (mRNA-1273) and was vaccinated with vial that might have had a temperature excursion. The patient's medical history was not provided. No relevant concomitant medications were reported. On 22 Dec 2020, the nurse reported a shipment was received. The vial arrived frozen and was placed in a freezer at recommended temperature. On 02 Jan 2021, the freezer had failed, and the temperature alarm system did not alert anyone. It was noted that the freezer temperature at 5:50 AM was -5 degrees Celsius (C), at 7:50 AM the freezer was a 1.5 C. It remained between from 9.7 C at 12:51 PM then went to 8.3 C at 1:51 PM then down to -8.7 C at 2:51 PM. On 03 Jan 2021 8:45 PM, the freezer returned to its normal temperature of -20.9 C, -1 C then went to 5.5 C at 11:56 PM. On 04 Jan 2021, the temperature climbed to 19.4 C. On the same day, the patient received their first of two planned doses of mRNA-1273 (Lot number: 025J20-2A, 025L20A, or 027L20A) intramuscularly for prophylaxis of COVID-19 infection and experienced vaccination with vial that might have had a temperature excursion No treatment information was provided. Action taken with mRNA-1273 in response to the event was not reported. The outcome of the event, vaccinated with vial that might have had a temperature excursion, was considered resolved on 04 Jan 2021.; Reporter's Comments: This report refers to a case of out of specification product use, product temperature excursion issue, and product storage error for mRNA-1273. There were no reported AEs associated with this case.4660.1%
 
vaccine expired in fridge3790.1%
 
temperature excursion with vaccine administered3780.1%
 
Error: Patient Too Young for Vaccine Administered-3310.1%
 
Error: Wrong Dose of Vaccine - Too Low3280.1%
 
Error: Improper Storage (temperature)-3140.1%
 
Patient had an ED visit and/or hospitalization within 6 weeks of receiving COVID vaccine.3060.1%
 
Error: Wrong Dose of Vaccine - Too High3040.1%
 
Error: Incorrect Reconstitution247< 0.1%
 
Tinnitus223< 0.1%
 
Shingles214< 0.1%
 
Hospitalization within 6 weeks after receiving vaccine208< 0.1%
 
CDC recommends using single-use vials of normal saline to dilute to each vial of the Pfizer vaccine. Staff member incorrectly used 100 ml bottles of normal saline to reconstitute multiple vials of vaccine each day. Staff member used a new bottle per day, however, and used the correct amount of normal saline to dilute each vial (1.8 ml per vial). We have since corrected this error and also notified local health authorities. Patient has not reported any adverse events to health clinic where error occurred.203< 0.1%
 
unknown179< 0.1%
 
None177< 0.1%
 
Pfizer Vaccine administered after being stored at regular freezer temps longer than recommended. Dose determined invalid, client contacted, and recommended dose repeated.168< 0.1%
 
Error: Wrong Vaccine Formulation (ex. different manufact. initial and booster)-151< 0.1%
 
NONE133< 0.1%
 
Error: Booster Given Too Early133< 0.1%
 
Death129< 0.1%
 
Vaccinated with vial that might have had a temperature excursion; Vaccinated with vial that might have had a temperature excursion; Vaccinated with vial that might have had a temperature excursion; A spontaneous report was received from a nurse concerning a patient who received Moderna's COVID-19 vaccine (mRNA-1273) and was vaccinated with vial that might have had a temperature excursion. The patient's medical history was not provided. No relevant concomitant medications were reported. On 22 Dec 2020, the nurse reported a shipment was received. The vial arrived frozen and was placed in a freezer at recommended temperature. On 02 Jan 2021, the freezer had failed, and the temperature alarm system did not alert anyone. It was noted that the freezer temperature at 5:50 AM was -5 degrees Celsius (C), at 7:50 AM the freezer was a 1.5 C. It remained between from 9.7 C at 12:51 PM then went to 8.3 C at 1:51 PM then down to -8.7 C at 2:51 PM. On 03 Jan 2021 8:45 PM, the freezer returned to its normal temperature of -20.9 C, -1 C then went to 5.5 C at 11:56 PM. On 04 Jan 2021, the temperature climbed to 19.4 C. On the same day, the patient received their first of two planned doses of mRNA-1273 (Lot number: 025J20-2A, 025L20A, or 027L20A) intramuscularly for prophylaxis of COVID-19 infection and experienced vaccination with vial that might have had a temperature excursion No treatment information was provided. Action taken with mRNA-1273 in response to the event was not reported. The outcome of the event, vaccinated with vial that might have had a temperature excursion, was considered resolved on 04 Jan 2021.; Reporter's Comments: This report refers to a case of out of specification product use, product temperature excursion issue, and product storage error for mRNA-1273. There were no reported AEs associated with this case.127< 0.1%
 
Other values (544579)56135498.6%
 
(Missing)129< 0.1%
 
2021-09-30T12:56:43.281150image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique540408 ?
Unique (%)94.9%
2021-09-30T12:56:43.369283image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length29450
Median length306
Mean length627.9968007
Min length1

Overview of Unicode Properties

Unique unicode characters99
Unique unicode categories14 ?
Unique unicode scripts2 ?
Unique unicode blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
5772651516.1%
 
e323809829.1%
 
t223743536.3%
 
a212423585.9%
 
n207854015.8%
 
o186339145.2%
 
i184728115.2%
 
r151751204.2%
 
s148086364.1%
 
d121109043.4%
 
h100098442.8%
 
c95107492.7%
 
l81198032.3%
 
m60724431.7%
 
u58618101.6%
 
p57988011.6%
 
f53377751.5%
 
w40549961.1%
 
g37798491.1%
 
.36147691.0%
 
v34972001.0%
 
y33854800.9%
 
I30251210.8%
 
,29323210.8%
 
b28213340.8%
 
Other values (74)4611151712.9%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter24746537669.2%
 
Space Separator5772651516.1%
 
Uppercase Letter275429597.7%
 
Decimal Number106407643.0%
 
Other Punctuation88048952.5%
 
Dash Punctuation21475570.6%
 
Open Punctuation16435880.5%
 
Close Punctuation16432770.5%
 
Math Symbol21407< 0.1%
 
Other Symbol7156< 0.1%
 
Connector Punctuation1006< 0.1%
 
Modifier Symbol162< 0.1%
 
Currency Symbol135< 0.1%
 
Control9< 0.1%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
I302512111.0%
 
A24414308.9%
 
T21928098.0%
 
N20218377.3%
 
O19565237.1%
 
E18667446.8%
 
C17871756.5%
 
R14914145.4%
 
S14451455.2%
 
D12718914.6%
 
V11661044.2%
 
M11417074.1%
 
P10936964.0%
 
L8488263.1%
 
H8160403.0%
 
F5814192.1%
 
B5482722.0%
 
U4960661.8%
 
G3061921.1%
 
Y2900371.1%
 
W2149280.8%
 
J1894370.7%
 
Z1364710.5%
 
X1141480.4%
 
K873850.3%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
e3238098213.1%
 
t223743539.0%
 
a212423588.6%
 
n207854018.4%
 
o186339147.5%
 
i184728117.5%
 
r151751206.1%
 
s148086366.0%
 
d121109044.9%
 
h100098444.0%
 
c95107493.8%
 
l81198033.3%
 
m60724432.5%
 
u58618102.4%
 
p57988012.3%
 
f53377752.2%
 
w40549961.6%
 
g37798491.5%
 
v34972001.4%
 
y33854801.4%
 
b28213341.1%
 
k16237730.7%
 
x6945730.3%
 
j4031280.2%
 
z3994590.2%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
57726515100.0%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
1275520225.9%
 
2263592924.8%
 
0166870215.7%
 
98760268.2%
 
37117596.7%
 
75069254.8%
 
64131293.9%
 
54030763.8%
 
43823373.6%
 
82876792.7%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.361476941.1%
 
,293232133.3%
 
;6653927.6%
 
/6154787.0%
 
:4987545.7%
 
'2650133.0%
 
"962641.1%
 
?361220.4%
 
%274680.3%
 
&233090.3%
 
#139180.2%
 
@58110.1%
 
!48600.1%
 
*4343< 0.1%
 
\1070< 0.1%
 
;3< 0.1%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-2147557100.0%
 

Most frequent Open Punctuation characters

ValueCountFrequency (%) 
(162555598.9%
 
[179221.1%
 
{111< 0.1%
 

Most frequent Close Punctuation characters

ValueCountFrequency (%) 
)162527398.9%
 
]178911.1%
 
}113< 0.1%
 

Most frequent Math Symbol characters

ValueCountFrequency (%) 
+715133.4%
 
=495623.2%
 
~433520.3%
 
>338515.8%
 
<12355.8%
 
|3451.6%
 

Most frequent Other Symbol characters

ValueCountFrequency (%) 
7156100.0%
 

Most frequent Connector Punctuation characters

ValueCountFrequency (%) 
_1006100.0%
 

Most frequent Currency Symbol characters

ValueCountFrequency (%) 
$135100.0%
 

Most frequent Modifier Symbol characters

ValueCountFrequency (%) 
^8753.7%
 
`7546.3%
 

Most frequent Control characters

ValueCountFrequency (%) 
777.8%
 
222.2%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin27500833576.9%
 
Common8263647123.1%
 

Most frequent Latin characters

ValueCountFrequency (%) 
e3238098211.8%
 
t223743538.1%
 
a212423587.7%
 
n207854017.6%
 
o186339146.8%
 
i184728116.7%
 
r151751205.5%
 
s148086365.4%
 
d121109044.4%
 
h100098443.6%
 
c95107493.5%
 
l81198033.0%
 
m60724432.2%
 
u58618102.1%
 
p57988012.1%
 
f53377751.9%
 
w40549961.5%
 
g37798491.4%
 
v34972001.3%
 
y33854801.2%
 
I30251211.1%
 
b28213341.0%
 
A24414300.9%
 
T21928090.8%
 
N20218370.7%
 
Other values (27)210925757.7%
 

Most frequent Common characters

ValueCountFrequency (%) 
5772651569.9%
 
.36147694.4%
 
,29323213.5%
 
127552023.3%
 
226359293.2%
 
-21475572.6%
 
016687022.0%
 
(16255552.0%
 
)16252732.0%
 
98760261.1%
 
37117590.9%
 
;6653920.8%
 
/6154780.7%
 
75069250.6%
 
:4987540.6%
 
64131290.5%
 
54030760.5%
 
43823370.5%
 
82876790.3%
 
'2650130.3%
 
"962640.1%
 
?36122< 0.1%
 
%27468< 0.1%
 
&23309< 0.1%
 
[17922< 0.1%
 
Other values (22)779950.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII357637647> 99.9%
 
Specials7156< 0.1%
 
None3< 0.1%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
5772651516.1%
 
e323809829.1%
 
t223743536.3%
 
a212423585.9%
 
n207854015.8%
 
o186339145.2%
 
i184728115.2%
 
r151751204.2%
 
s148086364.1%
 
d121109043.4%
 
h100098442.8%
 
c95107492.7%
 
l81198032.3%
 
m60724431.7%
 
u58618101.6%
 
p57988011.6%
 
f53377751.5%
 
w40549961.1%
 
g37798491.1%
 
.36147691.0%
 
v34972001.0%
 
y33854800.9%
 
I30251210.8%
 
,29323210.8%
 
b28213340.8%
 
Other values (72)4610435812.9%
 

Most frequent Specials characters

ValueCountFrequency (%) 
7156100.0%
 

Most frequent None characters

ValueCountFrequency (%) 
;3100.0%
 

DIED
Categorical

MISSING

Distinct1
Distinct (%)< 0.1%
Missing562319
Missing (%)98.7%
Memory size4.3 MiB
Y
7182 
ValueCountFrequency (%) 
Y71821.3%
 
(Missing)56231998.7%
 
2021-09-30T12:56:43.442984image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-09-30T12:56:43.479640image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:43.521448image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length2.97477792
Min length1

Overview of Unicode Properties

Unique unicode characters3
Unique unicode categories2 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n112463866.4%
 
a56231933.2%
 
Y71820.4%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter168695799.6%
 
Uppercase Letter71820.4%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n112463866.7%
 
a56231933.3%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
Y7182100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin1694139100.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n112463866.4%
 
a56231933.2%
 
Y71820.4%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII1694139100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n112463866.4%
 
a56231933.2%
 
Y71820.4%
 

DATEDIED
Categorical

HIGH CARDINALITY
MISSING

Distinct297
Distinct (%)4.6%
Missing563051
Missing (%)98.9%
Memory size4.3 MiB
04/01/2021
 
72
03/05/2021
 
57
02/01/2021
 
54
02/12/2021
 
54
03/01/2021
 
53
Other values (292)
6160 
ValueCountFrequency (%) 
04/01/202172< 0.1%
 
03/05/202157< 0.1%
 
02/01/202154< 0.1%
 
02/12/202154< 0.1%
 
03/01/202153< 0.1%
 
03/30/202151< 0.1%
 
04/06/202151< 0.1%
 
05/01/202150< 0.1%
 
03/19/202149< 0.1%
 
04/12/202149< 0.1%
 
02/13/202148< 0.1%
 
04/15/202148< 0.1%
 
02/11/202148< 0.1%
 
03/18/202148< 0.1%
 
03/12/202148< 0.1%
 
03/29/202147< 0.1%
 
04/10/202147< 0.1%
 
02/26/202147< 0.1%
 
04/03/202146< 0.1%
 
04/08/202146< 0.1%
 
03/24/202145< 0.1%
 
02/24/202145< 0.1%
 
03/13/202145< 0.1%
 
02/05/202145< 0.1%
 
02/21/202144< 0.1%
 
Other values (272)52130.9%
 
(Missing)56305198.9%
 
2021-09-30T12:56:43.605320image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique30 ?
Unique (%)0.5%
2021-09-30T12:56:43.679912image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length10
Median length3
Mean length3.079279931
Min length3

Overview of Unicode Properties

Unique unicode characters13
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n112610264.2%
 
a56305132.1%
 
2166500.9%
 
0154660.9%
 
/129000.7%
 
1102380.6%
 
322130.1%
 
417750.1%
 
514460.1%
 
811490.1%
 
69740.1%
 
79220.1%
 
9767< 0.1%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter168915396.3%
 
Decimal Number516002.9%
 
Other Punctuation129000.7%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n112610266.7%
 
a56305133.3%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
21665032.3%
 
01546630.0%
 
11023819.8%
 
322134.3%
 
417753.4%
 
514462.8%
 
811492.2%
 
69741.9%
 
79221.8%
 
97671.5%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
/12900100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin168915396.3%
 
Common645003.7%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n112610266.7%
 
a56305133.3%
 

Most frequent Common characters

ValueCountFrequency (%) 
21665025.8%
 
01546624.0%
 
/1290020.0%
 
11023815.9%
 
322133.4%
 
417752.8%
 
514462.2%
 
811491.8%
 
69741.5%
 
79221.4%
 
97671.2%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII1753653100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n112610264.2%
 
a56305132.1%
 
2166500.9%
 
0154660.9%
 
/129000.7%
 
1102380.6%
 
322130.1%
 
417750.1%
 
514460.1%
 
811490.1%
 
69740.1%
 
79220.1%
 
9767< 0.1%
 

L_THREAT
Categorical

MISSING

Distinct1
Distinct (%)< 0.1%
Missing560732
Missing (%)98.5%
Memory size4.3 MiB
Y
8769 
ValueCountFrequency (%) 
Y87691.5%
 
(Missing)56073298.5%
 
2021-09-30T12:56:43.740315image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-09-30T12:56:43.779066image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:43.822419image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length2.969204619
Min length1

Overview of Unicode Properties

Unique unicode characters3
Unique unicode categories2 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n112146466.3%
 
a56073233.2%
 
Y87690.5%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter168219699.5%
 
Uppercase Letter87690.5%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n112146466.7%
 
a56073233.3%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
Y8769100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin1690965100.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n112146466.3%
 
a56073233.2%
 
Y87690.5%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII1690965100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n112146466.3%
 
a56073233.2%
 
Y87690.5%
 

ER_VISIT
Categorical

MISSING

Distinct1
Distinct (%)1.9%
Missing569449
Missing (%)> 99.9%
Memory size4.3 MiB
Y
52 
ValueCountFrequency (%) 
Y52< 0.1%
 
(Missing)569449> 99.9%
 
2021-09-30T12:56:43.885023image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-09-30T12:56:43.922227image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:43.965844image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length2.999817384
Min length1

Overview of Unicode Properties

Unique unicode characters3
Unique unicode categories2 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n113889866.7%
 
a56944933.3%
 
Y52< 0.1%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter1708347> 99.9%
 
Uppercase Letter52< 0.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n113889866.7%
 
a56944933.3%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
Y52100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin1708399100.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n113889866.7%
 
a56944933.3%
 
Y52< 0.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII1708399100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n113889866.7%
 
a56944933.3%
 
Y52< 0.1%
 

HOSPITAL
Categorical

MISSING

Distinct1
Distinct (%)< 0.1%
Missing536233
Missing (%)94.2%
Memory size4.3 MiB
Y
33268 
ValueCountFrequency (%) 
Y332685.8%
 
(Missing)53623394.2%
 
2021-09-30T12:56:44.030053image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-09-30T12:56:44.068603image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:44.111525image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length2.883167896
Min length1

Overview of Unicode Properties

Unique unicode characters3
Unique unicode categories2 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n107246665.3%
 
a53623332.7%
 
Y332682.0%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter160869998.0%
 
Uppercase Letter332682.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n107246666.7%
 
a53623333.3%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
Y33268100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin1641967100.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n107246665.3%
 
a53623332.7%
 
Y332682.0%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII1641967100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n107246665.3%
 
a53623332.7%
 
Y332682.0%
 

HOSPDAYS
Real number (ℝ≥0)

MISSING
SKEWED

Distinct97
Distinct (%)0.4%
Missing546713
Missing (%)96.0%
Infinite0
Infinite (%)0.0%
Mean14.09193435
Minimum1
Maximum99999
Zeros0
Zeros (%)0.0%
Memory size4.3 MiB
2021-09-30T12:56:44.186583image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q36
95-th percentile16
Maximum99999
Range99998
Interquartile range (IQR)4

Descriptive statistics

Standard deviation936.828851
Coefficient of variation (CV)66.47979103
Kurtosis11387.79309
Mean14.09193435
Median Absolute Deviation (MAD)2
Skewness106.7097018
Sum321127
Variance877648.296
MonotocityNot monotonic
2021-09-30T12:56:44.267548image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
247360.8%
 
338950.7%
 
138930.7%
 
425490.4%
 
519230.3%
 
610900.2%
 
79860.2%
 
85670.1%
 
104480.1%
 
93790.1%
 
12279< 0.1%
 
11270< 0.1%
 
14257< 0.1%
 
13191< 0.1%
 
15156< 0.1%
 
16117< 0.1%
 
21107< 0.1%
 
2090< 0.1%
 
1785< 0.1%
 
1881< 0.1%
 
1967< 0.1%
 
3060< 0.1%
 
2546< 0.1%
 
2344< 0.1%
 
2444< 0.1%
 
Other values (72)4280.1%
 
(Missing)54671396.0%
 
ValueCountFrequency (%) 
138930.7%
 
247360.8%
 
338950.7%
 
425490.4%
 
519230.3%
 
610900.2%
 
79860.2%
 
85670.1%
 
93790.1%
 
104480.1%
 
ValueCountFrequency (%) 
999992< 0.1%
 
9991< 0.1%
 
7311< 0.1%
 
6991< 0.1%
 
1801< 0.1%
 
1711< 0.1%
 
1501< 0.1%
 
1361< 0.1%
 
1321< 0.1%
 
1271< 0.1%
 

X_STAY
Categorical

MISSING

Distinct1
Distinct (%)0.3%
Missing569195
Missing (%)99.9%
Memory size4.3 MiB
Y
306 
ValueCountFrequency (%) 
Y3060.1%
 
(Missing)56919599.9%
 
2021-09-30T12:56:44.339379image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-09-30T12:56:44.377606image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:44.541645image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length2.998925375
Min length1

Overview of Unicode Properties

Unique unicode characters3
Unique unicode categories2 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n113839066.7%
 
a56919533.3%
 
Y306< 0.1%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter1707585> 99.9%
 
Uppercase Letter306< 0.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n113839066.7%
 
a56919533.3%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
Y306100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin1707891100.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n113839066.7%
 
a56919533.3%
 
Y306< 0.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII1707891100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n113839066.7%
 
a56919533.3%
 
Y306< 0.1%
 

DISABLE
Categorical

MISSING

Distinct1
Distinct (%)< 0.1%
Missing560782
Missing (%)98.5%
Memory size4.3 MiB
Y
8719 
ValueCountFrequency (%) 
Y87191.5%
 
(Missing)56078298.5%
 
2021-09-30T12:56:44.606493image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-09-30T12:56:44.644873image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:44.687926image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length2.969380212
Min length1

Overview of Unicode Properties

Unique unicode characters3
Unique unicode categories2 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n112156466.3%
 
a56078233.2%
 
Y87190.5%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter168234699.5%
 
Uppercase Letter87190.5%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n112156466.7%
 
a56078233.3%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
Y8719100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin1691065100.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n112156466.3%
 
a56078233.2%
 
Y87190.5%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII1691065100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n112156466.3%
 
a56078233.2%
 
Y87190.5%
 

RECOVD
Categorical

MISSING

Distinct3
Distinct (%)< 0.1%
Missing49549
Missing (%)8.7%
Memory size4.3 MiB
N
198595 
Y
190505 
U
130852 
ValueCountFrequency (%) 
N19859534.9%
 
Y19050533.5%
 
U13085223.0%
 
(Missing)495498.7%
 
2021-09-30T12:56:44.758775image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-09-30T12:56:44.804966image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:44.854101image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length1
Mean length1.174008474
Min length1

Overview of Unicode Properties

Unique unicode characters5
Unique unicode categories2 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
N19859529.7%
 
Y19050528.5%
 
U13085219.6%
 
n9909814.8%
 
a495497.4%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter51995277.8%
 
Lowercase Letter14864722.2%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
N19859538.2%
 
Y19050536.6%
 
U13085225.2%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n9909866.7%
 
a4954933.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin668599100.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
N19859529.7%
 
Y19050528.5%
 
U13085219.6%
 
n9909814.8%
 
a495497.4%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII668599100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
N19859529.7%
 
Y19050528.5%
 
U13085219.6%
 
n9909814.8%
 
a495497.4%
 

VAX_DATE
Categorical

HIGH CARDINALITY
MISSING

Distinct1701
Distinct (%)0.3%
Missing39266
Missing (%)6.9%
Memory size4.3 MiB
04/01/2021
 
7797
04/08/2021
 
6402
04/07/2021
 
6116
04/09/2021
 
5958
04/06/2021
 
5436
Other values (1696)
498526 
ValueCountFrequency (%) 
04/01/202177971.4%
 
04/08/202164021.1%
 
04/07/202161161.1%
 
04/09/202159581.0%
 
04/06/202154361.0%
 
01/08/202151480.9%
 
03/01/202150730.9%
 
03/31/202150510.9%
 
03/12/202150480.9%
 
01/04/202149720.9%
 
03/11/202149550.9%
 
01/07/202148420.9%
 
04/02/202148190.8%
 
01/06/202147400.8%
 
03/26/202147260.8%
 
03/25/202146770.8%
 
03/18/202146420.8%
 
01/27/202146190.8%
 
01/20/202146050.8%
 
03/04/202146020.8%
 
03/05/202145950.8%
 
03/10/202145740.8%
 
02/04/202145680.8%
 
02/01/202145530.8%
 
01/28/202145450.8%
 
Other values (1676)40317270.8%
 
(Missing)392666.9%
 
2021-09-30T12:56:44.944157image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1001 ?
Unique (%)0.2%
2021-09-30T12:56:45.023826image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length10
Median length10
Mean length9.517363446
Min length3

Overview of Unicode Properties

Unique unicode characters13
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
2137879625.4%
 
0128806423.8%
 
/106047019.6%
 
186861516.0%
 
31914773.5%
 
41497702.8%
 
5990181.8%
 
n785321.4%
 
6760321.4%
 
8698761.3%
 
7631131.2%
 
9571191.1%
 
a392660.7%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number424188078.3%
 
Other Punctuation106047019.6%
 
Lowercase Letter1177982.2%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
2137879632.5%
 
0128806430.4%
 
186861520.5%
 
31914774.5%
 
41497703.5%
 
5990182.3%
 
6760321.8%
 
8698761.6%
 
7631131.5%
 
9571191.3%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
/1060470100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n7853266.7%
 
a3926633.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common530235097.8%
 
Latin1177982.2%
 

Most frequent Common characters

ValueCountFrequency (%) 
2137879626.0%
 
0128806424.3%
 
/106047020.0%
 
186861516.4%
 
31914773.6%
 
41497702.8%
 
5990181.9%
 
6760321.4%
 
8698761.3%
 
7631131.2%
 
9571191.1%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n7853266.7%
 
a3926633.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII5420148100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
2137879625.4%
 
0128806423.8%
 
/106047019.6%
 
186861516.0%
 
31914773.5%
 
41497702.8%
 
5990181.8%
 
n785321.4%
 
6760321.4%
 
8698761.3%
 
7631131.2%
 
9571191.1%
 
a392660.7%
 

ONSET_DATE
Categorical

HIGH CARDINALITY
MISSING

Distinct1126
Distinct (%)0.2%
Missing44284
Missing (%)7.8%
Memory size4.3 MiB
04/01/2021
 
8744
04/08/2021
 
6029
03/01/2021
 
6009
04/09/2021
 
5954
04/07/2021
 
5524
Other values (1121)
492957 
ValueCountFrequency (%) 
04/01/202187441.5%
 
04/08/202160291.1%
 
03/01/202160091.1%
 
04/09/202159541.0%
 
04/07/202155241.0%
 
04/10/202148680.9%
 
04/02/202148140.8%
 
04/06/202146480.8%
 
02/01/202145250.8%
 
03/12/202144580.8%
 
03/31/202143760.8%
 
03/25/202141620.7%
 
01/08/202141610.7%
 
03/11/202141590.7%
 
04/12/202141550.7%
 
03/26/202141550.7%
 
05/01/202141450.7%
 
01/07/202140580.7%
 
03/10/202140260.7%
 
04/14/202139570.7%
 
04/15/202139550.7%
 
03/18/202139530.7%
 
03/19/202139210.7%
 
03/24/202139140.7%
 
01/06/202138660.7%
 
Other values (1101)40868171.8%
 
(Missing)442847.8%
 
2021-09-30T12:56:45.108495image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique546 ?
Unique (%)0.1%
2021-09-30T12:56:45.181091image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length10
Median length10
Mean length9.455684889
Min length3

Overview of Unicode Properties

Unique unicode characters13
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
2134508125.0%
 
0127971123.8%
 
/105043419.5%
 
185820015.9%
 
31822513.4%
 
41580602.9%
 
51039521.9%
 
n885681.6%
 
6772981.4%
 
8731741.4%
 
7677591.3%
 
9562501.0%
 
a442840.8%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number420173678.0%
 
Other Punctuation105043419.5%
 
Lowercase Letter1328522.5%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
2134508132.0%
 
0127971130.5%
 
185820020.4%
 
31822514.3%
 
41580603.8%
 
51039522.5%
 
6772981.8%
 
8731741.7%
 
7677591.6%
 
9562501.3%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
/1050434100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n8856866.7%
 
a4428433.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common525217097.5%
 
Latin1328522.5%
 

Most frequent Common characters

ValueCountFrequency (%) 
2134508125.6%
 
0127971124.4%
 
/105043420.0%
 
185820016.3%
 
31822513.5%
 
41580603.0%
 
51039522.0%
 
6772981.5%
 
8731741.4%
 
7677591.3%
 
9562501.1%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n8856866.7%
 
a4428433.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII5385022100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
2134508125.0%
 
0127971123.8%
 
/105043419.5%
 
185820015.9%
 
31822513.4%
 
41580602.9%
 
51039521.9%
 
n885681.6%
 
6772981.4%
 
8731741.4%
 
7677591.3%
 
9562501.0%
 
a442840.8%
 

NUMDAYS
Real number (ℝ≥0)

MISSING
SKEWED
ZEROS

Distinct826
Distinct (%)0.2%
Missing66139
Missing (%)11.6%
Infinite0
Infinite (%)0.0%
Mean23.94008884
Minimum0
Maximum44224
Zeros221204
Zeros (%)38.8%
Memory size4.3 MiB
2021-09-30T12:56:45.253336image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q35
95-th percentile35
Maximum44224
Range44224
Interquartile range (IQR)5

Descriptive statistics

Standard deviation612.6793535
Coefficient of variation (CV)25.59219214
Kurtosis2408.760857
Mean23.94008884
Median Absolute Deviation (MAD)1
Skewness46.71933369
Sum12050531
Variance375375.9902
MonotocityNot monotonic
2021-09-30T12:56:45.329409image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
022120438.8%
 
110251818.0%
 
2275044.8%
 
7159712.8%
 
3153292.7%
 
8125662.2%
 
4101281.8%
 
582181.4%
 
680241.4%
 
971901.3%
 
1051280.9%
 
2842250.7%
 
1440230.7%
 
1137640.7%
 
1232500.6%
 
1328520.5%
 
2922510.4%
 
2121790.4%
 
1521540.4%
 
1617980.3%
 
1716210.3%
 
3115310.3%
 
1915120.3%
 
1814900.3%
 
2014270.3%
 
Other values (801)355056.2%
 
(Missing)6613911.6%
 
ValueCountFrequency (%) 
022120438.8%
 
110251818.0%
 
2275044.8%
 
3153292.7%
 
4101281.8%
 
582181.4%
 
680241.4%
 
7159712.8%
 
8125662.2%
 
971901.3%
 
ValueCountFrequency (%) 
442241< 0.1%
 
441952< 0.1%
 
368961< 0.1%
 
368901< 0.1%
 
366971< 0.1%
 
365731< 0.1%
 
365641< 0.1%
 
365611< 0.1%
 
365551< 0.1%
 
365532< 0.1%
 

LAB_DATA
Categorical

HIGH CARDINALITY
MISSING

Distinct125645
Distinct (%)56.3%
Missing346365
Missing (%)60.8%
Memory size4.3 MiB
None
43056 
none
23993 
None.
 
3130
NONE
 
2815
no
 
1921
Other values (125640)
148221 
ValueCountFrequency (%) 
None430567.6%
 
none239934.2%
 
None.31300.5%
 
NONE28150.5%
 
no19210.3%
 
No16930.3%
 
unknown13300.2%
 
N/a12940.2%
 
Unknown10590.2%
 
na7160.1%
 
None yet6830.1%
 
Na4250.1%
 
None at this time268< 0.1%
 
EKG268< 0.1%
 
UNKNOWN267< 0.1%
 
none yet242< 0.1%
 
none.240< 0.1%
 
NO203< 0.1%
 
None yet.195< 0.1%
 
see above185< 0.1%
 
SEE ABOVE176< 0.1%
 
See above173< 0.1%
 
None at this time.160< 0.1%
 
None to date157< 0.1%
 
0153< 0.1%
 
Other values (125620)13833424.3%
 
(Missing)34636560.8%
 
2021-09-30T12:56:45.673762image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique122560 ?
Unique (%)54.9%
2021-09-30T12:56:45.761109image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length32000
Median length3
Mean length35.863484
Min length1

Overview of Unicode Properties

Unique unicode characters97
Unique unicode categories14 ?
Unique unicode scripts2 ?
Unique unicode blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
317700315.6%
 
e16359138.0%
 
n15581057.6%
 
a13640066.7%
 
t13254076.5%
 
s9150674.5%
 
o9009994.4%
 
r7307733.6%
 
i7062833.5%
 
l5661852.8%
 
d4759862.3%
 
u4567782.2%
 
c3658371.8%
 
m3549541.7%
 
23036221.5%
 
h2996391.5%
 
12796911.4%
 
:2662561.3%
 
02530031.2%
 
T2464411.2%
 
p2193101.1%
 
N2176931.1%
 
g1968831.0%
 
R1894830.9%
 
.1857360.9%
 
Other values (72)323323715.8%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter1294733763.4%
 
Space Separator317700315.6%
 
Uppercase Letter19693179.6%
 
Decimal Number12256876.0%
 
Other Punctuation9269534.5%
 
Dash Punctuation1005550.5%
 
Close Punctuation309980.2%
 
Open Punctuation309920.2%
 
Math Symbol119050.1%
 
Connector Punctuation2373< 0.1%
 
Other Symbol855< 0.1%
 
Modifier Symbol271< 0.1%
 
Currency Symbol43< 0.1%
 
Other Number1< 0.1%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
T24644112.5%
 
N21769311.1%
 
R1894839.6%
 
D1573578.0%
 
C1537027.8%
 
I1088915.5%
 
E938194.8%
 
A895464.5%
 
U868334.4%
 
S823774.2%
 
P814104.1%
 
O735663.7%
 
B602093.1%
 
M597263.0%
 
L574832.9%
 
V451862.3%
 
H428002.2%
 
G352651.8%
 
F284271.4%
 
K170730.9%
 
W152680.8%
 
X104100.5%
 
Y71030.4%
 
J57820.3%
 
Q24740.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
e163591312.6%
 
n155810512.0%
 
a136400610.5%
 
t132540710.2%
 
s9150677.1%
 
o9009997.0%
 
r7307735.6%
 
i7062835.5%
 
l5661854.4%
 
d4759863.7%
 
u4567783.5%
 
c3658372.8%
 
m3549542.7%
 
h2996392.3%
 
p2193101.7%
 
g1968831.5%
 
y1667911.3%
 
v1557451.2%
 
f1524011.2%
 
w1457691.1%
 
b1424031.1%
 
k645840.5%
 
x295780.2%
 
z85190.1%
 
j5260< 0.1%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
230362224.8%
 
127969122.8%
 
025300320.6%
 
3734846.0%
 
4651945.3%
 
9600994.9%
 
5585164.8%
 
6455183.7%
 
8452423.7%
 
7413183.4%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
:26625628.7%
 
.18573620.0%
 
;15994417.3%
 
/15570816.8%
 
,12725813.7%
 
%89111.0%
 
'71670.8%
 
?50760.5%
 
*35140.4%
 
"24660.3%
 
&23020.2%
 
#9710.1%
 
@8900.1%
 
!7010.1%
 
\53< 0.1%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
3177003100.0%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-100555100.0%
 

Most frequent Open Punctuation characters

ValueCountFrequency (%) 
(2904793.7%
 
[15024.8%
 
{4431.4%
 

Most frequent Close Punctuation characters

ValueCountFrequency (%) 
)2906093.7%
 
]14934.8%
 
}4451.4%
 

Most frequent Math Symbol characters

ValueCountFrequency (%) 
=335128.1%
 
+224618.9%
 
|219418.4%
 
<206317.3%
 
>177114.9%
 
~2802.4%
 

Most frequent Other Symbol characters

ValueCountFrequency (%) 
855100.0%
 

Most frequent Connector Punctuation characters

ValueCountFrequency (%) 
_2373100.0%
 

Most frequent Modifier Symbol characters

ValueCountFrequency (%) 
^26095.9%
 
`114.1%
 

Most frequent Other Number characters

ValueCountFrequency (%) 
²1100.0%
 

Most frequent Currency Symbol characters

ValueCountFrequency (%) 
$43100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin1491665473.0%
 
Common550763627.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
e163591311.0%
 
n155810510.4%
 
a13640069.1%
 
t13254078.9%
 
s9150676.1%
 
o9009996.0%
 
r7307734.9%
 
i7062834.7%
 
l5661853.8%
 
d4759863.2%
 
u4567783.1%
 
c3658372.5%
 
m3549542.4%
 
h2996392.0%
 
T2464411.7%
 
p2193101.5%
 
N2176931.5%
 
g1968831.3%
 
R1894831.3%
 
y1667911.1%
 
D1573571.1%
 
v1557451.0%
 
C1537021.0%
 
f1524011.0%
 
w1457691.0%
 
Other values (27)12591478.4%
 

Most frequent Common characters

ValueCountFrequency (%) 
317700357.7%
 
23036225.5%
 
12796915.1%
 
:2662564.8%
 
02530034.6%
 
.1857363.4%
 
;1599442.9%
 
/1557082.8%
 
,1272582.3%
 
-1005551.8%
 
3734841.3%
 
4651941.2%
 
9600991.1%
 
5585161.1%
 
6455180.8%
 
8452420.8%
 
7413180.8%
 
)290600.5%
 
(290470.5%
 
%89110.2%
 
'71670.1%
 
?50760.1%
 
*35140.1%
 
=33510.1%
 
"2466< 0.1%
 
Other values (20)208970.4%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII20423434> 99.9%
 
Specials855< 0.1%
 
Latin 1 Sup1< 0.1%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
317700315.6%
 
e16359138.0%
 
n15581057.6%
 
a13640066.7%
 
t13254076.5%
 
s9150674.5%
 
o9009994.4%
 
r7307733.6%
 
i7062833.5%
 
l5661852.8%
 
d4759862.3%
 
u4567782.2%
 
c3658371.8%
 
m3549541.7%
 
23036221.5%
 
h2996391.5%
 
12796911.4%
 
:2662561.3%
 
02530031.2%
 
T2464411.2%
 
p2193101.1%
 
N2176931.1%
 
g1968831.0%
 
R1894830.9%
 
.1857360.9%
 
Other values (70)323238115.8%
 

Most frequent Specials characters

ValueCountFrequency (%) 
855100.0%
 

Most frequent Latin 1 Sup characters

ValueCountFrequency (%) 
²1100.0%
 

V_ADMINBY
Categorical

Distinct9
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.3 MiB
UNK
162869 
PVT
122742 
PHM
100348 
OTH
82036 
PUB
58015 
Other values (4)
43491 
ValueCountFrequency (%) 
UNK16286928.6%
 
PVT12274221.6%
 
PHM10034817.6%
 
OTH8203614.4%
 
PUB5801510.2%
 
WRK191673.4%
 
SCH87421.5%
 
SEN86611.5%
 
MIL69211.2%
 
2021-09-30T12:56:45.845418image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-09-30T12:56:45.897556image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:45.959162image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length3
Min length3

Overview of Unicode Properties

Unique unicode characters17
Unique unicode categories1 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
P28110516.5%
 
U22088412.9%
 
T20477812.0%
 
H19112611.2%
 
K18203610.7%
 
N17153010.0%
 
V1227427.2%
 
M1072696.3%
 
O820364.8%
 
B580153.4%
 
W191671.1%
 
R191671.1%
 
S174031.0%
 
C87420.5%
 
E86610.5%
 
I69210.4%
 
L69210.4%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter1708503100.0%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
P28110516.5%
 
U22088412.9%
 
T20477812.0%
 
H19112611.2%
 
K18203610.7%
 
N17153010.0%
 
V1227427.2%
 
M1072696.3%
 
O820364.8%
 
B580153.4%
 
W191671.1%
 
R191671.1%
 
S174031.0%
 
C87420.5%
 
E86610.5%
 
I69210.4%
 
L69210.4%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin1708503100.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
P28110516.5%
 
U22088412.9%
 
T20477812.0%
 
H19112611.2%
 
K18203610.7%
 
N17153010.0%
 
V1227427.2%
 
M1072696.3%
 
O820364.8%
 
B580153.4%
 
W191671.1%
 
R191671.1%
 
S174031.0%
 
C87420.5%
 
E86610.5%
 
I69210.4%
 
L69210.4%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII1708503100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
P28110516.5%
 
U22088412.9%
 
T20477812.0%
 
H19112611.2%
 
K18203610.7%
 
N17153010.0%
 
V1227427.2%
 
M1072696.3%
 
O820364.8%
 
B580153.4%
 
W191671.1%
 
R191671.1%
 
S174031.0%
 
C87420.5%
 
E86610.5%
 
I69210.4%
 
L69210.4%
 

V_FUNDBY
Categorical

MISSING

Distinct5
Distinct (%)1.3%
Missing569108
Missing (%)99.9%
Memory size4.3 MiB
OTH
190 
UNK
83 
PUB
71 
PVT
45 
MIL
 
4
ValueCountFrequency (%) 
OTH190< 0.1%
 
UNK83< 0.1%
 
PUB71< 0.1%
 
PVT45< 0.1%
 
MIL4< 0.1%
 
(Missing)56910899.9%
 
2021-09-30T12:56:46.023223image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-09-30T12:56:46.069259image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:46.117902image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length3
Min length3

Overview of Unicode Properties

Unique unicode characters14
Unique unicode categories2 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n113821666.6%
 
a56910833.3%
 
T235< 0.1%
 
O190< 0.1%
 
H190< 0.1%
 
U154< 0.1%
 
P116< 0.1%
 
N83< 0.1%
 
K83< 0.1%
 
B71< 0.1%
 
V45< 0.1%
 
M4< 0.1%
 
I4< 0.1%
 
L4< 0.1%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter170732499.9%
 
Uppercase Letter11790.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n113821666.7%
 
a56910833.3%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
T23519.9%
 
O19016.1%
 
H19016.1%
 
U15413.1%
 
P1169.8%
 
N837.0%
 
K837.0%
 
B716.0%
 
V453.8%
 
M40.3%
 
I40.3%
 
L40.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin1708503100.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n113821666.6%
 
a56910833.3%
 
T235< 0.1%
 
O190< 0.1%
 
H190< 0.1%
 
U154< 0.1%
 
P116< 0.1%
 
N83< 0.1%
 
K83< 0.1%
 
B71< 0.1%
 
V45< 0.1%
 
M4< 0.1%
 
I4< 0.1%
 
L4< 0.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII1708503100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n113821666.6%
 
a56910833.3%
 
T235< 0.1%
 
O190< 0.1%
 
H190< 0.1%
 
U154< 0.1%
 
P116< 0.1%
 
N83< 0.1%
 
K83< 0.1%
 
B71< 0.1%
 
V45< 0.1%
 
M4< 0.1%
 
I4< 0.1%
 
L4< 0.1%
 

OTHER_MEDS
Categorical

HIGH CARDINALITY
MISSING

Distinct218020
Distinct (%)65.0%
Missing234118
Missing (%)41.1%
Memory size4.3 MiB
None
32076 
none
 
14425
unknown
 
6127
Unknown
 
4979
No
 
2547
Other values (218015)
275229 
ValueCountFrequency (%) 
None320765.6%
 
none144252.5%
 
unknown61271.1%
 
Unknown49790.9%
 
No25470.4%
 
NONE22760.4%
 
no15930.3%
 
UNKNOWN12930.2%
 
None.11440.2%
 
Tylenol7710.1%
 
N/a7030.1%
 
Levothyroxine6880.1%
 
Multivitamin6400.1%
 
Birth control6280.1%
 
Synthroid5230.1%
 
Zyrtec5110.1%
 
None reported4860.1%
 
Vitamin D4750.1%
 
Ibuprofen4460.1%
 
LEVOTHYROXINE4320.1%
 
na3780.1%
 
none known3740.1%
 
SYNTHROID3740.1%
 
TYLENOL3700.1%
 
none reported3570.1%
 
Other values (217995)26076745.8%
 
(Missing)23411841.1%
 
2021-09-30T12:56:46.669550image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique210441 ?
Unique (%)62.7%
2021-09-30T12:56:46.757790image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length240
Median length4
Mean length29.98529063
Min length1

Overview of Unicode Properties

Unique unicode characters98
Unique unicode categories14 ?
Unique unicode scripts2 ?
Unique unicode blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
198036711.6%
 
n13413247.9%
 
a11518386.7%
 
i11174326.5%
 
e9182695.4%
 
o8417544.9%
 
t7818594.6%
 
l6598143.9%
 
r6472253.8%
 
m5474253.2%
 
,4801462.8%
 
s3838112.2%
 
p2926841.7%
 
d2920851.7%
 
c2909331.7%
 
u2523651.5%
 
A2518601.5%
 
g2322021.4%
 
I2267531.3%
 
y2096091.2%
 
02066791.2%
 
N2053211.2%
 
O1946231.1%
 
L1945531.1%
 
T1792551.0%
 
Other values (73)319646718.7%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter1080525563.3%
 
Uppercase Letter281378816.5%
 
Space Separator198036711.6%
 
Other Punctuation7199824.2%
 
Decimal Number5980043.5%
 
Dash Punctuation541960.3%
 
Open Punctuation499940.3%
 
Close Punctuation490250.3%
 
Math Symbol5571< 0.1%
 
Other Symbol240< 0.1%
 
Connector Punctuation201< 0.1%
 
Modifier Symbol19< 0.1%
 
Currency Symbol9< 0.1%
 
Control2< 0.1%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
A2518609.0%
 
I2267538.1%
 
N2053217.3%
 
O1946236.9%
 
L1945536.9%
 
T1792556.4%
 
E1778246.3%
 
C1608855.7%
 
M1590885.7%
 
R1468155.2%
 
D1365864.9%
 
S1237204.4%
 
P1144564.1%
 
V1042173.7%
 
B777582.8%
 
H579892.1%
 
F539961.9%
 
U515281.8%
 
Z447001.6%
 
G440511.6%
 
Y356921.3%
 
X303481.1%
 
Q138860.5%
 
W129240.5%
 
K104300.4%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n134132412.4%
 
a115183810.7%
 
i111743210.3%
 
e9182698.5%
 
o8417547.8%
 
t7818597.2%
 
l6598146.1%
 
r6472256.0%
 
m5474255.1%
 
s3838113.6%
 
p2926842.7%
 
d2920852.7%
 
c2909332.7%
 
u2523652.3%
 
g2322022.1%
 
y2096091.9%
 
v1677431.6%
 
h1600871.5%
 
b1337731.2%
 
x1050491.0%
 
f967100.9%
 
z785020.7%
 
w413240.4%
 
k409130.4%
 
q157850.1%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
1980367100.0%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
,48014666.7%
 
;12200216.9%
 
.613248.5%
 
/321224.5%
 
:68591.0%
 
'41730.6%
 
?41190.6%
 
&34610.5%
 
%33450.5%
 
*8060.1%
 
"7730.1%
 
@3650.1%
 
#319< 0.1%
 
!132< 0.1%
 
\35< 0.1%
 
;1< 0.1%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
020667934.6%
 
111543519.3%
 
28808514.7%
 
57941813.3%
 
3440177.4%
 
4224553.8%
 
8173972.9%
 
6113911.9%
 
792321.5%
 
938950.7%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-54196100.0%
 

Most frequent Open Punctuation characters

ValueCountFrequency (%) 
(3516870.3%
 
[1480829.6%
 
{18< 0.1%
 

Most frequent Close Punctuation characters

ValueCountFrequency (%) 
)3482171.0%
 
]1419028.9%
 
}14< 0.1%
 

Most frequent Math Symbol characters

ValueCountFrequency (%) 
+345962.1%
 
=182332.7%
 
~1071.9%
 
>781.4%
 
|771.4%
 
<270.5%
 

Most frequent Other Symbol characters

ValueCountFrequency (%) 
240100.0%
 

Most frequent Modifier Symbol characters

ValueCountFrequency (%) 
`1578.9%
 
^421.1%
 

Most frequent Connector Punctuation characters

ValueCountFrequency (%) 
_201100.0%
 

Most frequent Currency Symbol characters

ValueCountFrequency (%) 
$9100.0%
 

Most frequent Control characters

ValueCountFrequency (%) 
2100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin1361904379.8%
 
Common345761020.2%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n13413249.8%
 
a11518388.5%
 
i11174328.2%
 
e9182696.7%
 
o8417546.2%
 
t7818595.7%
 
l6598144.8%
 
r6472254.8%
 
m5474254.0%
 
s3838112.8%
 
p2926842.1%
 
d2920852.1%
 
c2909332.1%
 
u2523651.9%
 
A2518601.8%
 
g2322021.7%
 
I2267531.7%
 
y2096091.5%
 
N2053211.5%
 
O1946231.4%
 
L1945531.4%
 
T1792551.3%
 
E1778241.3%
 
v1677431.2%
 
C1608851.2%
 
Other values (27)189959713.9%
 

Most frequent Common characters

ValueCountFrequency (%) 
198036757.3%
 
,48014613.9%
 
02066796.0%
 
;1220023.5%
 
11154353.3%
 
2880852.5%
 
5794182.3%
 
.613241.8%
 
-541961.6%
 
3440171.3%
 
(351681.0%
 
)348211.0%
 
/321220.9%
 
4224550.6%
 
8173970.5%
 
[148080.4%
 
]141900.4%
 
6113910.3%
 
792320.3%
 
:68590.2%
 
'41730.1%
 
?41190.1%
 
938950.1%
 
&34610.1%
 
+34590.1%
 
Other values (21)83910.2%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII17076412> 99.9%
 
Specials240< 0.1%
 
None1< 0.1%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
198036711.6%
 
n13413247.9%
 
a11518386.7%
 
i11174326.5%
 
e9182695.4%
 
o8417544.9%
 
t7818594.6%
 
l6598143.9%
 
r6472253.8%
 
m5474253.2%
 
,4801462.8%
 
s3838112.2%
 
p2926841.7%
 
d2920851.7%
 
c2909331.7%
 
u2523651.5%
 
A2518601.5%
 
g2322021.4%
 
I2267531.3%
 
y2096091.2%
 
02066791.2%
 
N2053211.2%
 
O1946231.1%
 
L1945531.1%
 
T1792551.0%
 
Other values (71)319622618.7%
 

Most frequent Specials characters

ValueCountFrequency (%) 
240100.0%
 

Most frequent None characters

ValueCountFrequency (%) 
;1100.0%
 

CUR_ILL
Categorical

HIGH CARDINALITY
MISSING

Distinct51645
Distinct (%)19.5%
Missing304713
Missing (%)53.5%
Memory size4.3 MiB
None
96724 
none
46819 
No
 
9841
no
 
6366
NONE
 
5423
Other values (51640)
99615 
ValueCountFrequency (%) 
None9672417.0%
 
none468198.2%
 
No98411.7%
 
no63661.1%
 
NONE54231.0%
 
unknown47400.8%
 
Unknown37400.7%
 
None.35420.6%
 
N/a16850.3%
 
None known10380.2%
 
None reported10260.2%
 
UNKNOWN9890.2%
 
none known9380.2%
 
none reported8600.2%
 
NO8500.1%
 
Asthma7060.1%
 
na6350.1%
 
Hypertension6070.1%
 
Diabetes5320.1%
 
Na5110.1%
 
Seasonal allergies4190.1%
 
No.3580.1%
 
UTI3210.1%
 
03190.1%
 
Abstains from alcohol; Non-smoker3160.1%
 
Other values (51620)7548313.3%
 
(Missing)30471353.5%
 
2021-09-30T12:56:46.935836image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique48436 ?
Unique (%)18.3%
2021-09-30T12:56:47.020950image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4668
Median length3
Mean length9.865250456
Min length1

Overview of Unicode Properties

Unique unicode characters97
Unique unicode categories14 ?
Unique unicode scripts2 ?
Unique unicode blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n105248418.7%
 
a5392709.6%
 
5239069.3%
 
e4971188.8%
 
o4095187.3%
 
i2577394.6%
 
t2193543.9%
 
s2059343.7%
 
r2055963.7%
 
N1526012.7%
 
l1438322.6%
 
d1120162.0%
 
c992501.8%
 
h988511.8%
 
m711171.3%
 
u704071.3%
 
y694141.2%
 
p688091.2%
 
g645901.1%
 
f444370.8%
 
b376080.7%
 
w367300.7%
 
v338930.6%
 
,324600.6%
 
k293730.5%
 
Other values (72)5419639.6%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter438252578.0%
 
Space Separator5239069.3%
 
Uppercase Letter4558578.1%
 
Other Punctuation1132012.0%
 
Decimal Number938521.7%
 
Open Punctuation184310.3%
 
Close Punctuation184150.3%
 
Dash Punctuation113780.2%
 
Math Symbol563< 0.1%
 
Other Symbol66< 0.1%
 
Connector Punctuation41< 0.1%
 
Control31< 0.1%
 
Modifier Symbol3< 0.1%
 
Currency Symbol1< 0.1%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
N15260133.5%
 
A281826.2%
 
D254495.6%
 
O246955.4%
 
I238575.2%
 
C229515.0%
 
E223554.9%
 
S209744.6%
 
H187164.1%
 
P163863.6%
 
T161283.5%
 
R134693.0%
 
M105882.3%
 
U103312.3%
 
B91352.0%
 
L86921.9%
 
V77771.7%
 
F68471.5%
 
G51871.1%
 
K33570.7%
 
W29050.6%
 
Y22990.5%
 
J17430.4%
 
X5950.1%
 
Z4590.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n105248424.0%
 
a53927012.3%
 
e49711811.3%
 
o4095189.3%
 
i2577395.9%
 
t2193545.0%
 
s2059344.7%
 
r2055964.7%
 
l1438323.3%
 
d1120162.6%
 
c992502.3%
 
h988512.3%
 
m711171.6%
 
u704071.6%
 
y694141.6%
 
p688091.6%
 
g645901.5%
 
f444371.0%
 
b376080.9%
 
w367300.8%
 
v338930.8%
 
k293730.7%
 
x85050.2%
 
z35220.1%
 
j2175< 0.1%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
523906100.0%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
,3246028.7%
 
.2904925.7%
 
;2482021.9%
 
/1832816.2%
 
'24642.2%
 
:21711.9%
 
?21201.9%
 
"6290.6%
 
&4640.4%
 
#2080.2%
 
*1580.1%
 
%1570.1%
 
!1240.1%
 
@25< 0.1%
 
\24< 0.1%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-11378100.0%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
22700828.8%
 
12330424.8%
 
01697518.1%
 
960596.5%
 
352605.6%
 
438654.1%
 
536523.9%
 
826782.9%
 
626562.8%
 
723952.6%
 

Most frequent Open Punctuation characters

ValueCountFrequency (%) 
(1832699.4%
 
[1000.5%
 
{5< 0.1%
 

Most frequent Close Punctuation characters

ValueCountFrequency (%) 
)1831299.4%
 
]1000.5%
 
}3< 0.1%
 

Most frequent Math Symbol characters

ValueCountFrequency (%) 
+34360.9%
 
>6611.7%
 
~5910.5%
 
=458.0%
 
|285.0%
 
<223.9%
 

Most frequent Other Symbol characters

ValueCountFrequency (%) 
66100.0%
 

Most frequent Modifier Symbol characters

ValueCountFrequency (%) 
`266.7%
 
^133.3%
 

Most frequent Currency Symbol characters

ValueCountFrequency (%) 
$1100.0%
 

Most frequent Connector Punctuation characters

ValueCountFrequency (%) 
_41100.0%
 

Most frequent Control characters

ValueCountFrequency (%) 
31100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin483838286.1%
 
Common77988813.9%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n105248421.8%
 
a53927011.1%
 
e49711810.3%
 
o4095188.5%
 
i2577395.3%
 
t2193544.5%
 
s2059344.3%
 
r2055964.2%
 
N1526013.2%
 
l1438323.0%
 
d1120162.3%
 
c992502.1%
 
h988512.0%
 
m711171.5%
 
u704071.5%
 
y694141.4%
 
p688091.4%
 
g645901.3%
 
f444370.9%
 
b376080.8%
 
w367300.8%
 
v338930.7%
 
k293730.6%
 
A281820.6%
 
D254490.5%
 
Other values (27)2648105.5%
 

Most frequent Common characters

ValueCountFrequency (%) 
52390667.2%
 
,324604.2%
 
.290493.7%
 
2270083.5%
 
;248203.2%
 
1233043.0%
 
/183282.4%
 
(183262.3%
 
)183122.3%
 
0169752.2%
 
-113781.5%
 
960590.8%
 
352600.7%
 
438650.5%
 
536520.5%
 
826780.3%
 
626560.3%
 
'24640.3%
 
723950.3%
 
:21710.3%
 
?21200.3%
 
"6290.1%
 
&4640.1%
 
+343< 0.1%
 
#208< 0.1%
 
Other values (20)10580.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII5618204> 99.9%
 
Specials66< 0.1%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n105248418.7%
 
a5392709.6%
 
5239069.3%
 
e4971188.8%
 
o4095187.3%
 
i2577394.6%
 
t2193543.9%
 
s2059343.7%
 
r2055963.7%
 
N1526012.7%
 
l1438322.6%
 
d1120162.0%
 
c992501.8%
 
h988511.8%
 
m711171.3%
 
u704071.3%
 
y694141.2%
 
p688091.2%
 
g645901.1%
 
f444370.8%
 
b376080.7%
 
w367300.7%
 
v338930.6%
 
,324600.6%
 
k293730.5%
 
Other values (71)5418979.6%
 

Most frequent Specials characters

ValueCountFrequency (%) 
66100.0%
 

HISTORY
Categorical

HIGH CARDINALITY
MISSING

Distinct146407
Distinct (%)40.9%
Missing211582
Missing (%)37.2%
Memory size4.3 MiB
None
50414 
none
 
23493
Comments: Unknown
 
6979
No
 
5681
Asthma
 
5171
Other values (146402)
266181 
ValueCountFrequency (%) 
None504148.9%
 
none234934.1%
 
Comments: Unknown69791.2%
 
No56811.0%
 
Asthma51710.9%
 
Medical History/Concurrent Conditions: No adverse event41300.7%
 
Comments: List of non-encoded Patient Relevant History: Patient Other Relevant History 1: None40380.7%
 
unknown38390.7%
 
no34350.6%
 
NONE31920.6%
 
Unknown31100.5%
 
Comments: No medical history was provided by the reporter.25040.4%
 
Medical History/Concurrent Conditions: No adverse event (No reported medical history)21870.4%
 
Hypertension19980.4%
 
None.17070.3%
 
Medical History/Concurrent Conditions: No adverse event (No medical history reported)16940.3%
 
High blood pressure16200.3%
 
Medical History/Concurrent Conditions: COVID-1916200.3%
 
asthma15290.3%
 
Medical History/Concurrent Conditions: No adverse event (No reported medical history.)14430.3%
 
Hypothyroidism13770.2%
 
Diabetes12140.2%
 
HTN9890.2%
 
N/a9670.2%
 
Migraines9260.2%
 
Other values (146382)22266239.1%
 
(Missing)21158237.2%
 
2021-09-30T12:56:47.423890image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique137188 ?
Unique (%)38.3%
2021-09-30T12:56:47.513084image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length10700
Median length4
Mean length28.39772538
Min length1

Overview of Unicode Properties

Unique unicode characters98
Unique unicode categories14 ?
Unique unicode scripts2 ?
Unique unicode blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
173132810.7%
 
n14003918.7%
 
e13663708.4%
 
i11111706.9%
 
o10670886.6%
 
a10154576.3%
 
t9063705.6%
 
r8935395.5%
 
s8419045.2%
 
l4915103.0%
 
d4803013.0%
 
c4017772.5%
 
h3560232.2%
 
y3398012.1%
 
m2918061.8%
 
p2658011.6%
 
u2469161.5%
 
C2039331.3%
 
,1892441.2%
 
g1801901.1%
 
H1587071.0%
 
N1450040.9%
 
b1287780.8%
 
v1172900.7%
 
f998710.6%
 
Other values (73)174196410.8%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter1217811175.3%
 
Space Separator173132810.7%
 
Uppercase Letter14409438.9%
 
Other Punctuation4996463.1%
 
Decimal Number1655421.0%
 
Close Punctuation589230.4%
 
Open Punctuation587620.4%
 
Dash Punctuation366500.2%
 
Math Symbol1310< 0.1%
 
Connector Punctuation851< 0.1%
 
Other Symbol402< 0.1%
 
Control53< 0.1%
 
Modifier Symbol10< 0.1%
 
Currency Symbol2< 0.1%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
C20393314.2%
 
H15870711.0%
 
N14500410.1%
 
A983516.8%
 
D943356.5%
 
M924976.4%
 
S720235.0%
 
P711574.9%
 
I692004.8%
 
O676674.7%
 
E612654.3%
 
R571414.0%
 
T567763.9%
 
L355022.5%
 
B354162.5%
 
U241541.7%
 
V237971.7%
 
G231561.6%
 
F211121.5%
 
Y95010.7%
 
K94110.7%
 
W46650.3%
 
J28160.2%
 
X19270.1%
 
Z9770.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n140039111.5%
 
e136637011.2%
 
i11111709.1%
 
o10670888.8%
 
a10154578.3%
 
t9063707.4%
 
r8935397.3%
 
s8419046.9%
 
l4915104.0%
 
d4803013.9%
 
c4017773.3%
 
h3560232.9%
 
y3398012.8%
 
m2918062.4%
 
p2658012.2%
 
u2469162.0%
 
g1801901.5%
 
b1287781.1%
 
v1172901.0%
 
f998710.8%
 
w708740.6%
 
k557840.5%
 
x315410.3%
 
z89770.1%
 
j63130.1%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
1731328100.0%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
,18924437.9%
 
:9582719.2%
 
/7491515.0%
 
;6309912.6%
 
.5590811.2%
 
'92401.8%
 
?74511.5%
 
&13760.3%
 
"11420.2%
 
*5360.1%
 
%3840.1%
 
#3200.1%
 
!153< 0.1%
 
@33< 0.1%
 
\18< 0.1%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
14121024.9%
 
23775122.8%
 
03052018.4%
 
91716710.4%
 
391955.6%
 
573814.5%
 
465283.9%
 
856773.4%
 
651283.1%
 
749853.0%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-36650100.0%
 

Most frequent Open Punctuation characters

ValueCountFrequency (%) 
(5826699.2%
 
[4890.8%
 
{7< 0.1%
 

Most frequent Close Punctuation characters

ValueCountFrequency (%) 
)5844699.2%
 
]4730.8%
 
}4< 0.1%
 

Most frequent Math Symbol characters

ValueCountFrequency (%) 
+57744.0%
 
=29422.4%
 
>18314.0%
 
~13510.3%
 
<957.3%
 
|262.0%
 

Most frequent Other Symbol characters

ValueCountFrequency (%) 
402100.0%
 

Most frequent Connector Punctuation characters

ValueCountFrequency (%) 
_851100.0%
 

Most frequent Modifier Symbol characters

ValueCountFrequency (%) 
^990.0%
 
`110.0%
 

Most frequent Currency Symbol characters

ValueCountFrequency (%) 
$2100.0%
 

Most frequent Control characters

ValueCountFrequency (%) 
3158.5%
 
2241.5%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin1361905484.2%
 
Common255347915.8%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n140039110.3%
 
e136637010.0%
 
i11111708.2%
 
o10670887.8%
 
a10154577.5%
 
t9063706.7%
 
r8935396.6%
 
s8419046.2%
 
l4915103.6%
 
d4803013.5%
 
c4017773.0%
 
h3560232.6%
 
y3398012.5%
 
m2918062.1%
 
p2658012.0%
 
u2469161.8%
 
C2039331.5%
 
g1801901.3%
 
H1587071.2%
 
N1450041.1%
 
b1287780.9%
 
v1172900.9%
 
f998710.7%
 
A983510.7%
 
D943350.7%
 
Other values (27)9163716.7%
 

Most frequent Common characters

ValueCountFrequency (%) 
173132867.8%
 
,1892447.4%
 
:958273.8%
 
/749152.9%
 
;630992.5%
 
)584462.3%
 
(582662.3%
 
.559082.2%
 
1412101.6%
 
2377511.5%
 
-366501.4%
 
0305201.2%
 
9171670.7%
 
'92400.4%
 
391950.4%
 
?74510.3%
 
573810.3%
 
465280.3%
 
856770.2%
 
651280.2%
 
749850.2%
 
&13760.1%
 
"1142< 0.1%
 
_851< 0.1%
 
+577< 0.1%
 
Other values (21)36170.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII16172131> 99.9%
 
Specials402< 0.1%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
173132810.7%
 
n14003918.7%
 
e13663708.4%
 
i11111706.9%
 
o10670886.6%
 
a10154576.3%
 
t9063705.6%
 
r8935395.5%
 
s8419045.2%
 
l4915103.0%
 
d4803013.0%
 
c4017772.5%
 
h3560232.2%
 
y3398012.1%
 
m2918061.8%
 
p2658011.6%
 
u2469161.5%
 
C2039331.3%
 
,1892441.2%
 
g1801901.1%
 
H1587071.0%
 
N1450040.9%
 
b1287780.8%
 
v1172900.7%
 
f998710.6%
 
Other values (72)174156210.8%
 

Most frequent Specials characters

ValueCountFrequency (%) 
402100.0%
 

PRIOR_VAX
Categorical

HIGH CARDINALITY
MISSING

Distinct23877
Distinct (%)89.1%
Missing542711
Missing (%)95.3%
Memory size4.3 MiB
Flu shot
 
199
Flu
 
146
Flu vaccine
 
144
Shingles
 
133
Shingrix
 
89
Other values (23872)
26079 
ValueCountFrequency (%) 
Flu shot199< 0.1%
 
Flu146< 0.1%
 
Flu vaccine144< 0.1%
 
Shingles133< 0.1%
 
Shingrix89< 0.1%
 
Tetanus82< 0.1%
 
Influenza80< 0.1%
 
flu vaccine67< 0.1%
 
Moderna61< 0.1%
 
flu shot61< 0.1%
 
Sore arm54< 0.1%
 
Flu Vaccine48< 0.1%
 
MMR48< 0.1%
 
unknown48< 0.1%
 
Shingles vaccine42< 0.1%
 
influenza41< 0.1%
 
Pneumonia38< 0.1%
 
Penicillin37< 0.1%
 
Flu Shot35< 0.1%
 
fainting34< 0.1%
 
Influenza vaccine32< 0.1%
 
flu32< 0.1%
 
sore arm29< 0.1%
 
shingles28< 0.1%
 
Tdap27< 0.1%
 
Other values (23852)251554.4%
 
(Missing)54271195.3%
 
2021-09-30T12:56:47.643353image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique23377 ?
Unique (%)87.3%
2021-09-30T12:56:47.734564image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length128
Median length3
Mean length5.428116895
Min length2

Overview of Unicode Properties

Unique unicode characters93
Unique unicode categories11 ?
Unique unicode scripts2 ?
Unique unicode blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n116587937.7%
 
a64007620.7%
 
2281377.4%
 
e1273894.1%
 
i829032.7%
 
t779562.5%
 
s743932.4%
 
o706712.3%
 
r602011.9%
 
l465451.5%
 
c463481.5%
 
d418621.4%
 
h418551.4%
 
f292400.9%
 
u283620.9%
 
v243120.8%
 
m231660.7%
 
g216130.7%
 
,182920.6%
 
y172470.6%
 
p165610.5%
 
2154460.5%
 
1150540.5%
 
w135070.4%
 
0117950.4%
 
Other values (68)1525084.9%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter267599886.6%
 
Space Separator2281377.4%
 
Uppercase Letter739202.4%
 
Decimal Number626412.0%
 
Other Punctuation401751.3%
 
Dash Punctuation61880.2%
 
Open Punctuation20040.1%
 
Close Punctuation18730.1%
 
Math Symbol365< 0.1%
 
Other Symbol9< 0.1%
 
Connector Punctuation8< 0.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n116587943.6%
 
a64007623.9%
 
e1273894.8%
 
i829033.1%
 
t779562.9%
 
s743932.8%
 
o706712.6%
 
r602012.2%
 
l465451.7%
 
c463481.7%
 
d418621.6%
 
h418551.6%
 
f292401.1%
 
u283621.1%
 
v243120.9%
 
m231660.9%
 
g216130.8%
 
y172470.6%
 
p165610.6%
 
w135070.5%
 
b88730.3%
 
k54630.2%
 
x43820.2%
 
z41050.2%
 
j28470.1%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
228137100.0%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
,1829245.5%
 
.1039125.9%
 
/680216.9%
 
;13823.4%
 
'7081.8%
 
:6881.7%
 
#5581.4%
 
"5431.4%
 
?4121.0%
 
&3160.8%
 
@410.1%
 
!210.1%
 
\7< 0.1%
 
*7< 0.1%
 
%7< 0.1%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
21544624.7%
 
11505424.0%
 
01179518.8%
 
946507.4%
 
335285.6%
 
529114.6%
 
427614.4%
 
624283.9%
 
821213.4%
 
719473.1%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
I769910.4%
 
S744910.1%
 
F57687.8%
 
A48866.6%
 
P47986.5%
 
M44576.0%
 
T43785.9%
 
C42705.8%
 
V41235.6%
 
D39125.3%
 
O35714.8%
 
E33544.5%
 
R29324.0%
 
N27023.7%
 
H25603.5%
 
L16092.2%
 
B13081.8%
 
U9141.2%
 
G8701.2%
 
W6260.8%
 
Y5870.8%
 
J4580.6%
 
Z3090.4%
 
K1880.3%
 
X1280.2%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-6188100.0%
 

Most frequent Open Punctuation characters

ValueCountFrequency (%) 
(199699.6%
 
[70.3%
 
{1< 0.1%
 

Most frequent Close Punctuation characters

ValueCountFrequency (%) 
)186499.5%
 
]80.4%
 
}10.1%
 

Most frequent Math Symbol characters

ValueCountFrequency (%) 
~18149.6%
 
+12434.0%
 
=267.1%
 
>164.4%
 
<133.6%
 
|51.4%
 

Most frequent Other Symbol characters

ValueCountFrequency (%) 
9100.0%
 

Most frequent Connector Punctuation characters

ValueCountFrequency (%) 
_8100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin274991889.0%
 
Common34140011.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n116587942.4%
 
a64007623.3%
 
e1273894.6%
 
i829033.0%
 
t779562.8%
 
s743932.7%
 
o706712.6%
 
r602012.2%
 
l465451.7%
 
c463481.7%
 
d418621.5%
 
h418551.5%
 
f292401.1%
 
u283621.0%
 
v243120.9%
 
m231660.8%
 
g216130.8%
 
y172470.6%
 
p165610.6%
 
w135070.5%
 
b88730.3%
 
I76990.3%
 
S74490.3%
 
F57680.2%
 
k54630.2%
 
Other values (27)645802.3%
 

Most frequent Common characters

ValueCountFrequency (%) 
22813766.8%
 
,182925.4%
 
2154464.5%
 
1150544.4%
 
0117953.5%
 
.103913.0%
 
/68022.0%
 
-61881.8%
 
946501.4%
 
335281.0%
 
529110.9%
 
427610.8%
 
624280.7%
 
821210.6%
 
(19960.6%
 
719470.6%
 
)18640.5%
 
;13820.4%
 
'7080.2%
 
:6880.2%
 
#5580.2%
 
"5430.2%
 
?4120.1%
 
&3160.1%
 
~1810.1%
 
Other values (16)3010.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII3091309> 99.9%
 
Specials9< 0.1%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n116587937.7%
 
a64007620.7%
 
2281377.4%
 
e1273894.1%
 
i829032.7%
 
t779562.5%
 
s743932.4%
 
o706712.3%
 
r602011.9%
 
l465451.5%
 
c463481.5%
 
d418621.4%
 
h418551.4%
 
f292400.9%
 
u283620.9%
 
v243120.8%
 
m231660.7%
 
g216130.7%
 
,182920.6%
 
y172470.6%
 
p165610.5%
 
2154460.5%
 
1150540.5%
 
w135070.4%
 
0117950.4%
 
Other values (67)1524994.9%
 

Most frequent Specials characters

ValueCountFrequency (%) 
9100.0%
 

SPLTTYPE
Categorical

HIGH CARDINALITY
MISSING

Distinct77868
Distinct (%)47.3%
Missing404977
Missing (%)71.1%
Memory size4.3 MiB
USMODERNATX, INC.MOD20210
51470 
vsafe
10605 
USMODERNATX, INC.MOD20212
9847 
USMODERNATX, INC.MOD20211
9249 
USMODERNATX, INC.MOD20213
 
1523
Other values (77863)
81830 
ValueCountFrequency (%) 
USMODERNATX, INC.MOD20210514709.0%
 
vsafe106051.9%
 
USMODERNATX, INC.MOD2021298471.7%
 
USMODERNATX, INC.MOD2021192491.6%
 
USMODERNATX, INC.MOD2021315230.3%
 
USGLAXOSMITHKLINEUS2021AM12330.2%
 
USMODERNATX, INC.MOD202008070.1%
 
USGLAXOSMITHKLINEUS202113167< 0.1%
 
USGLAXOSMITHKLINEUS2020AM124< 0.1%
 
USGLAXOSMITHKLINEUS202112117< 0.1%
 
USGLAXOSMITHKLINEUS202115115< 0.1%
 
CA134B100194< 0.1%
 
USEMERGENT BIOSOLUTIONS2090< 0.1%
 
USGLAXOSMITHKLINEUS20202474< 0.1%
 
USGLAXOSMITHKLINEUS20211472< 0.1%
 
USGLAXOSMITHKLINEUS20202370< 0.1%
 
USBAVARIAN NORDIC A/SUSBN67< 0.1%
 
Unknown56< 0.1%
 
USGLAXOSMITHKLINEUS2021GS56< 0.1%
 
TX2954< 0.1%
 
USGLAXOSMITHKLINEUS20211153< 0.1%
 
USGLAXOSMITHKLINEUS20211649< 0.1%
 
USGLAXOSMITHKLINEUS20211046< 0.1%
 
USGLAXOSMITHKLINEUS20210046< 0.1%
 
unknown45< 0.1%
 
Other values (77843)7839513.8%
 
(Missing)40497771.1%
 
2021-09-30T12:56:47.971655image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique77692 ?
Unique (%)47.2%
2021-09-30T12:56:48.055158image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length25
Median length3
Mean length8.465825345
Min length1

Overview of Unicode Properties

Unique unicode characters78
Unique unicode categories10 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n81064116.8%
 
a4159618.6%
 
23616107.5%
 
02884506.0%
 
N2228344.6%
 
12157294.5%
 
I1990214.1%
 
O1627473.4%
 
S1604173.3%
 
U1560883.2%
 
M1500663.1%
 
C1473733.1%
 
D1462103.0%
 
E1362932.8%
 
1341842.8%
 
R1339962.8%
 
A800461.7%
 
T756731.6%
 
X754181.6%
 
F740051.5%
 
,729581.5%
 
.729511.5%
 
P606101.3%
 
Z601771.2%
 
3550841.1%
 
Other values (53)3527547.3%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter208231743.2%
 
Lowercase Letter127258926.4%
 
Decimal Number118569824.6%
 
Other Punctuation1461783.0%
 
Space Separator1341842.8%
 
Dash Punctuation319< 0.1%
 
Open Punctuation5< 0.1%
 
Close Punctuation3< 0.1%
 
Connector Punctuation2< 0.1%
 
Modifier Symbol1< 0.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n81064163.7%
 
a41596132.7%
 
e111160.9%
 
s108060.8%
 
f107160.8%
 
v106870.8%
 
o505< 0.1%
 
i289< 0.1%
 
t259< 0.1%
 
r252< 0.1%
 
c218< 0.1%
 
k168< 0.1%
 
w164< 0.1%
 
d137< 0.1%
 
u128< 0.1%
 
l113< 0.1%
 
p105< 0.1%
 
m80< 0.1%
 
h79< 0.1%
 
z46< 0.1%
 
b45< 0.1%
 
j28< 0.1%
 
g23< 0.1%
 
y20< 0.1%
 
x2< 0.1%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
236161030.5%
 
028845024.3%
 
121572918.2%
 
3550844.6%
 
4532894.5%
 
5492924.2%
 
6427423.6%
 
7401763.4%
 
8397843.4%
 
9395423.3%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
N22283410.7%
 
I1990219.6%
 
O1627477.8%
 
S1604177.7%
 
U1560887.5%
 
M1500667.2%
 
C1473737.1%
 
D1462107.0%
 
E1362936.5%
 
R1339966.4%
 
A800463.8%
 
T756733.6%
 
X754183.6%
 
F740053.6%
 
P606102.9%
 
Z601772.9%
 
J276701.3%
 
L49840.2%
 
G26070.1%
 
H24760.1%
 
K24190.1%
 
B406< 0.1%
 
V379< 0.1%
 
Q333< 0.1%
 
W44< 0.1%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-319100.0%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
134184100.0%
 

Most frequent Open Punctuation characters

ValueCountFrequency (%) 
(5100.0%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
,7295849.9%
 
.7295149.9%
 
/1000.1%
 
?73< 0.1%
 
#64< 0.1%
 
:13< 0.1%
 
'12< 0.1%
 
;3< 0.1%
 
&3< 0.1%
 
@1< 0.1%
 

Most frequent Close Punctuation characters

ValueCountFrequency (%) 
)3100.0%
 

Most frequent Connector Punctuation characters

ValueCountFrequency (%) 
_2100.0%
 

Most frequent Modifier Symbol characters

ValueCountFrequency (%) 
`1100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin335490669.6%
 
Common146639030.4%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n81064124.2%
 
a41596112.4%
 
N2228346.6%
 
I1990215.9%
 
O1627474.9%
 
S1604174.8%
 
U1560884.7%
 
M1500664.5%
 
C1473734.4%
 
D1462104.4%
 
E1362934.1%
 
R1339964.0%
 
A800462.4%
 
T756732.3%
 
X754182.2%
 
F740052.2%
 
P606101.8%
 
Z601771.8%
 
J276700.8%
 
e111160.3%
 
s108060.3%
 
f107160.3%
 
v106870.3%
 
L49840.1%
 
G26070.1%
 
Other values (27)87440.3%
 

Most frequent Common characters

ValueCountFrequency (%) 
236161024.7%
 
028845019.7%
 
121572914.7%
 
1341849.2%
 
,729585.0%
 
.729515.0%
 
3550843.8%
 
4532893.6%
 
5492923.4%
 
6427422.9%
 
7401762.7%
 
8397842.7%
 
9395422.7%
 
-319< 0.1%
 
/100< 0.1%
 
?73< 0.1%
 
#64< 0.1%
 
:13< 0.1%
 
'12< 0.1%
 
(5< 0.1%
 
)3< 0.1%
 
;3< 0.1%
 
&3< 0.1%
 
_2< 0.1%
 
@1< 0.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII4821296100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n81064116.8%
 
a4159618.6%
 
23616107.5%
 
02884506.0%
 
N2228344.6%
 
12157294.5%
 
I1990214.1%
 
O1627473.4%
 
S1604173.3%
 
U1560883.2%
 
M1500663.1%
 
C1473733.1%
 
D1462103.0%
 
E1362932.8%
 
1341842.8%
 
R1339962.8%
 
A800461.7%
 
T756731.6%
 
X754181.6%
 
F740051.5%
 
,729581.5%
 
.729511.5%
 
P606101.3%
 
Z601771.2%
 
3550841.1%
 
Other values (53)3527547.3%
 

FORM_VERS
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.3 MiB
2
569108 
1
 
393
ValueCountFrequency (%) 
256910899.9%
 
13930.1%
 
2021-09-30T12:56:48.122714image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-09-30T12:56:48.160769image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:48.200304image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

Overview of Unicode Properties

Unique unicode characters2
Unique unicode categories1 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
256910899.9%
 
13930.1%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number569501100.0%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
256910899.9%
 
13930.1%
 

Most occurring scripts

ValueCountFrequency (%) 
Common569501100.0%
 

Most frequent Common characters

ValueCountFrequency (%) 
256910899.9%
 
13930.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII569501100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
256910899.9%
 
13930.1%
 

TODAYS_DATE
Categorical

HIGH CARDINALITY

Distinct367
Distinct (%)0.1%
Missing2650
Missing (%)0.5%
Memory size4.3 MiB
08/12/2021
 
14154
08/11/2021
 
12061
08/13/2021
 
8260
08/17/2021
 
8180
08/10/2021
 
7996
Other values (362)
516200 
ValueCountFrequency (%) 
08/12/2021141542.5%
 
08/11/2021120612.1%
 
08/13/202182601.5%
 
08/17/202181801.4%
 
08/10/202179961.4%
 
04/13/202158211.0%
 
08/16/202155191.0%
 
08/14/202149450.9%
 
04/14/202148330.8%
 
08/09/202147660.8%
 
04/15/202145500.8%
 
04/12/202143580.8%
 
04/09/202143090.8%
 
01/06/202142730.8%
 
04/08/202142000.7%
 
04/16/202141380.7%
 
04/21/202138720.7%
 
04/07/202138340.7%
 
04/22/202138290.7%
 
04/20/202137990.7%
 
04/19/202135930.6%
 
04/23/202135410.6%
 
04/01/202134920.6%
 
01/27/202134870.6%
 
04/27/202134770.6%
 
Other values (342)43156475.8%
 
2021-09-30T12:56:48.277965image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique59 ?
Unique (%)< 0.1%
2021-09-30T12:56:48.352188image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length10
Median length10
Mean length9.967427625
Min length3

Overview of Unicode Properties

Unique unicode characters13
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
2141446524.9%
 
0134312223.7%
 
/113370220.0%
 
193068316.4%
 
31578932.8%
 
41550292.7%
 
81524342.7%
 
51134812.0%
 
61021271.8%
 
7898811.6%
 
9756931.3%
 
n53000.1%
 
a2650< 0.1%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number453480879.9%
 
Other Punctuation113370220.0%
 
Lowercase Letter79500.1%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
2141446531.2%
 
0134312229.6%
 
193068320.5%
 
31578933.5%
 
41550293.4%
 
81524343.4%
 
51134812.5%
 
61021272.3%
 
7898812.0%
 
9756931.7%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
/1133702100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n530066.7%
 
a265033.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common566851099.9%
 
Latin79500.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
2141446525.0%
 
0134312223.7%
 
/113370220.0%
 
193068316.4%
 
31578932.8%
 
41550292.7%
 
81524342.7%
 
51134812.0%
 
61021271.8%
 
7898811.6%
 
9756931.3%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n530066.7%
 
a265033.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII5676460100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
2141446524.9%
 
0134312223.7%
 
/113370220.0%
 
193068316.4%
 
31578932.8%
 
41550292.7%
 
81524342.7%
 
51134812.0%
 
61021271.8%
 
7898811.6%
 
9756931.3%
 
n53000.1%
 
a2650< 0.1%
 

BIRTH_DEFECT
Categorical

MISSING

Distinct1
Distinct (%)0.3%
Missing569178
Missing (%)99.9%
Memory size4.3 MiB
Y
323 
ValueCountFrequency (%) 
Y3230.1%
 
(Missing)56917899.9%
 
2021-09-30T12:56:48.568296image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-09-30T12:56:48.605177image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:48.647366image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length2.998865674
Min length1

Overview of Unicode Properties

Unique unicode characters3
Unique unicode categories2 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n113835666.7%
 
a56917833.3%
 
Y323< 0.1%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter1707534> 99.9%
 
Uppercase Letter323< 0.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n113835666.7%
 
a56917833.3%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
Y323100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin1707857100.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n113835666.7%
 
a56917833.3%
 
Y323< 0.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII1707857100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n113835666.7%
 
a56917833.3%
 
Y323< 0.1%
 

OFC_VISIT
Categorical

MISSING

Distinct1
Distinct (%)< 0.1%
Missing462554
Missing (%)81.2%
Memory size4.3 MiB
Y
106947 
ValueCountFrequency (%) 
Y10694718.8%
 
(Missing)46255481.2%
 
2021-09-30T12:56:48.709920image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-09-30T12:56:48.748412image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:48.790806image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length2.62441857
Min length1

Overview of Unicode Properties

Unique unicode characters3
Unique unicode categories2 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n92510861.9%
 
a46255430.9%
 
Y1069477.2%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter138766292.8%
 
Uppercase Letter1069477.2%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
Y106947100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n92510866.7%
 
a46255433.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin1494609100.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n92510861.9%
 
a46255430.9%
 
Y1069477.2%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII1494609100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n92510861.9%
 
a46255430.9%
 
Y1069477.2%
 

ER_ED_VISIT
Categorical

MISSING

Distinct1
Distinct (%)< 0.1%
Missing499046
Missing (%)87.6%
Memory size4.3 MiB
Y
70455 
ValueCountFrequency (%) 
Y7045512.4%
 
(Missing)49904687.6%
 
2021-09-30T12:56:48.853752image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-09-30T12:56:48.892880image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:48.935212image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length2.752572866
Min length1

Overview of Unicode Properties

Unique unicode characters3
Unique unicode categories2 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n99809263.7%
 
a49904631.8%
 
Y704554.5%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter149713895.5%
 
Uppercase Letter704554.5%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n99809266.7%
 
a49904633.3%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
Y70455100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin1567593100.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n99809263.7%
 
a49904631.8%
 
Y704554.5%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII1567593100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n99809263.7%
 
a49904631.8%
 
Y704554.5%
 

ALLERGIES
Categorical

HIGH CARDINALITY
MISSING

Distinct99925
Distinct (%)33.7%
Missing273103
Missing (%)48.0%
Memory size4.3 MiB
None
53465 
none
25465 
NKDA
 
7445
NKA
 
7351
No
 
7169
Other values (99920)
195503 
ValueCountFrequency (%) 
None534659.4%
 
none254654.5%
 
NKDA74451.3%
 
NKA73511.3%
 
No71691.3%
 
Penicillin70261.2%
 
no40350.7%
 
Sulfa34680.6%
 
NONE33010.6%
 
None known27200.5%
 
unknown24930.4%
 
Unknown22930.4%
 
penicillin20360.4%
 
No known allergies19630.3%
 
none known16270.3%
 
None.15900.3%
 
Amoxicillin13680.2%
 
nka13500.2%
 
Codeine12550.2%
 
N/a11330.2%
 
Latex10670.2%
 
PCN10620.2%
 
sulfa9890.2%
 
no known allergies9830.2%
 
Sulfa drugs9780.2%
 
Other values (99900)15276626.8%
 
(Missing)27310348.0%
 
2021-09-30T12:56:49.210012image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique93440 ?
Unique (%)31.5%
2021-09-30T12:56:49.296815image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length10220
Median length3
Mean length11.90314152
Min length1

Overview of Unicode Properties

Unique unicode characters98
Unique unicode categories14 ?
Unique unicode scripts2 ?
Unique unicode blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n106976015.8%
 
a6172409.1%
 
5884828.7%
 
e5513958.1%
 
i4432126.5%
 
o4077916.0%
 
l3354294.9%
 
s2439833.6%
 
t2418723.6%
 
r2349443.5%
 
c1863442.7%
 
,1548742.3%
 
d1420962.1%
 
N1286401.9%
 
u1132491.7%
 
p1031651.5%
 
h1031091.5%
 
m1029291.5%
 
g813521.2%
 
f760831.1%
 
y757511.1%
 
A586120.9%
 
S483490.7%
 
x451340.7%
 
P438950.6%
 
Other values (73)5811618.6%
 

Most occurring categories

ValueCountFrequency (%) 
Lowercase Letter534079778.8%
 
Space Separator5884828.7%
 
Uppercase Letter5748708.5%
 
Other Punctuation2085383.1%
 
Decimal Number191590.3%
 
Dash Punctuation168240.2%
 
Open Punctuation147130.2%
 
Close Punctuation146140.2%
 
Math Symbol714< 0.1%
 
Other Symbol102< 0.1%
 
Connector Punctuation20< 0.1%
 
Control11< 0.1%
 
Modifier Symbol6< 0.1%
 
Currency Symbol1< 0.1%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
N12864022.4%
 
A5861210.2%
 
S483498.4%
 
P438957.6%
 
C363006.3%
 
I283164.9%
 
D266414.6%
 
E241844.2%
 
L235004.1%
 
K222273.9%
 
O191663.3%
 
T174313.0%
 
M173723.0%
 
B136152.4%
 
R133312.3%
 
H97651.7%
 
F80231.4%
 
U79291.4%
 
G78241.4%
 
V73671.3%
 
W37840.7%
 
Z30840.5%
 
Y26810.5%
 
X17000.3%
 
Q5960.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n106976020.0%
 
a61724011.6%
 
e55139510.3%
 
i4432128.3%
 
o4077917.6%
 
l3354296.3%
 
s2439834.6%
 
t2418724.5%
 
r2349444.4%
 
c1863443.5%
 
d1420962.7%
 
u1132492.1%
 
p1031651.9%
 
h1031091.9%
 
m1029291.9%
 
g813521.5%
 
f760831.4%
 
y757511.4%
 
x451340.8%
 
v395230.7%
 
w371200.7%
 
b369140.7%
 
k337690.6%
 
z129530.2%
 
q42400.1%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
588482100.0%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
,15487474.3%
 
.2309211.1%
 
/99644.8%
 
;93514.5%
 
:38171.8%
 
?27001.3%
 
'15100.7%
 
&14780.7%
 
"10960.5%
 
*2960.1%
 
#1720.1%
 
!96< 0.1%
 
%56< 0.1%
 
\24< 0.1%
 
@12< 0.1%
 

Most frequent Open Punctuation characters

ValueCountFrequency (%) 
(1324890.0%
 
[14569.9%
 
{90.1%
 

Most frequent Close Punctuation characters

ValueCountFrequency (%) 
)1319090.3%
 
]14169.7%
 
}80.1%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-16824100.0%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
0439322.9%
 
1428322.4%
 
2411821.5%
 
311596.0%
 
511596.0%
 
910785.6%
 
48934.7%
 
67734.0%
 
86813.6%
 
76223.2%
 

Most frequent Math Symbol characters

ValueCountFrequency (%) 
=35149.2%
 
>16523.1%
 
+16322.8%
 
~223.1%
 
|91.3%
 
<40.6%
 

Most frequent Other Symbol characters

ValueCountFrequency (%) 
102100.0%
 

Most frequent Connector Punctuation characters

ValueCountFrequency (%) 
_20100.0%
 

Most frequent Modifier Symbol characters

ValueCountFrequency (%) 
`583.3%
 
^116.7%
 

Most frequent Currency Symbol characters

ValueCountFrequency (%) 
$1100.0%
 

Most frequent Control characters

ValueCountFrequency (%) 
1090.9%
 
19.1%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin591566787.3%
 
Common86318412.7%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n106976018.1%
 
a61724010.4%
 
e5513959.3%
 
i4432127.5%
 
o4077916.9%
 
l3354295.7%
 
s2439834.1%
 
t2418724.1%
 
r2349444.0%
 
c1863443.2%
 
d1420962.4%
 
N1286402.2%
 
u1132491.9%
 
p1031651.7%
 
h1031091.7%
 
m1029291.7%
 
g813521.4%
 
f760831.3%
 
y757511.3%
 
A586121.0%
 
S483490.8%
 
x451340.8%
 
P438950.7%
 
v395230.7%
 
w371200.6%
 
Other values (27)3846906.5%
 

Most frequent Common characters

ValueCountFrequency (%) 
58848268.2%
 
,15487417.9%
 
.230922.7%
 
-168241.9%
 
(132481.5%
 
)131901.5%
 
/99641.2%
 
;93511.1%
 
043930.5%
 
142830.5%
 
241180.5%
 
:38170.4%
 
?27000.3%
 
'15100.2%
 
&14780.2%
 
[14560.2%
 
]14160.2%
 
311590.1%
 
511590.1%
 
"10960.1%
 
910780.1%
 
48930.1%
 
67730.1%
 
86810.1%
 
76220.1%
 
Other values (21)15270.2%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII6778749> 99.9%
 
Specials102< 0.1%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n106976015.8%
 
a6172409.1%
 
5884828.7%
 
e5513958.1%
 
i4432126.5%
 
o4077916.0%
 
l3354294.9%
 
s2439833.6%
 
t2418723.6%
 
r2349443.5%
 
c1863442.7%
 
,1548742.3%
 
d1420962.1%
 
N1286401.9%
 
u1132491.7%
 
p1031651.5%
 
h1031091.5%
 
m1029291.5%
 
g813521.2%
 
f760831.1%
 
y757511.1%
 
A586120.9%
 
S483490.7%
 
x451340.7%
 
P438950.6%
 
Other values (72)5810598.6%
 

Most frequent Specials characters

ValueCountFrequency (%) 
102100.0%
 

Interactions

2021-09-30T12:56:25.687575image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:25.773960image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:25.834735image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:25.900691image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:25.962037image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:26.026677image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:26.090765image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:26.148302image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:26.200509image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:26.258449image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:26.310630image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:26.366688image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:26.422548image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:26.488529image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:26.548609image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:26.614093image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:26.674383image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:26.738363image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:26.801867image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:26.859620image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:26.911405image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:26.968486image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:27.019051image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:27.073765image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:27.128078image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:27.191717image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:27.249445image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:27.312435image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:27.369298image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:27.605409image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:27.665250image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:27.726851image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:27.782735image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:27.843861image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:27.898893image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:27.957284image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Correlations

2021-09-30T12:56:49.368031image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2021-09-30T12:56:49.453238image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2021-09-30T12:56:49.537700image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2021-09-30T12:56:49.628610image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.
2021-09-30T12:56:49.723594image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Missing values

2021-09-30T12:56:30.814467image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:32.746913image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:38.177950image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-09-30T12:56:39.183368image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Sample

First rows

VAERS_IDRECVDATESTATEAGE_YRSCAGE_YRCAGE_MOSEXRPT_DATESYMPTOM_TEXTDIEDDATEDIEDL_THREATER_VISITHOSPITALHOSPDAYSX_STAYDISABLERECOVDVAX_DATEONSET_DATENUMDAYSLAB_DATAV_ADMINBYV_FUNDBYOTHER_MEDSCUR_ILLHISTORYPRIOR_VAXSPLTTYPEFORM_VERSTODAYS_DATEBIRTH_DEFECTOFC_VISITER_ED_VISITALLERGIES
091660001/01/2021TX33.033.0NaNFNaNRight side of epiglottis swelled up and hinder swallowing pictures taken Benadryl Tylenol takenNaNNaNNaNNaNNaNNaNNaNNaNY12/28/202012/30/20202.0NonePVTNaNNoneNoneNoneNaNNaN201/01/2021NaNYNaNPcn and bee venom
191660101/01/2021CA73.073.0NaNFNaNApproximately 30 min post vaccination administration patient demonstrated SOB and anxiousness. Assessed at time of event: Heart sounds normal, Lung sounds clear. Vitals within normal limits for patient. O2 91% on 3 liters NC Continuous flow. 2 consecutive nebulized albuterol treatments were administered. At approximately 1.5 hours post reaction, patients' SOB and anxiousness had subsided and the patient stated that they were feel "much better".NaNNaNNaNNaNNaNNaNNaNNaNY12/31/202012/31/20200.0NaNSENNaNPatient residing at nursing facility. See patients chart.Patient residing at nursing facility. See patients chart.Patient residing at nursing facility. See patients chart.NaNNaN201/01/2021NaNYNaN"Dairy"
291660201/01/2021WA23.023.0NaNFNaNAbout 15 minutes after receiving the vaccine, the patient complained about her left arm hurting. She also complained of chest tightness and difficulty swallowing. Patient also had vision changes. We gave the patient 1 tablet of Benadryl 25 mg and called EMS services. EMS checked her out and we advised the patient to go to the ER to be observed and given more Benadryl. Patient was able to walk out of facility herself.NaNNaNNaNNaNNaNNaNNaNNaNU12/31/202012/31/20200.0NaNSENNaNNoneNoneNoneNaNNaN201/01/2021NaNNaNYShellfish
391660301/01/2021WA58.058.0NaNFNaNextreme fatigue, dizziness,. could not lift my left arm for 72 hoursNaNNaNNaNNaNNaNNaNNaNNaNY12/23/202012/23/20200.0noneWRKNaNnonekidney infectiondiverticulitis, mitral valve prolapse, osteoarthritisgot measles from measel shot, mums from mumps shot, headaches and nausea from flu shotNaN201/01/2021NaNNaNNaNDiclofenac, novacaine, lidocaine, pickles, tomatoes, milk
491660401/01/2021TX47.047.0NaNFNaNInjection site swelling, redness, warm to the touch and itchyNaNNaNNaNNaNNaNNaNNaNNaNN12/22/202012/29/20207.0NaNPUBNaNNaNaNaNNaNNaN201/01/2021NaNNaNNaNNa
591660501/01/2021TX40.040.0NaNMNaNAdverse Events: Inflammation in the eye, confusion, headaches, inflammation in ears, cold chills, shivering, and fever like symptoms Treatments: Primary care physician ran a series of bloodwork and found that after Flu shot I had big drop in white blood cell count and referred me to ophthalmologist and otolaryngologist ophthalmologist prescribed Cequa to treat the inflammation in eyes along with fortified caster oil. otolaryngologist prescribed Prednisone to treat the inflammtion Time course: Still having adverse eventsNaNNaNNaNNaNNaNNaNNaNNaNN09/25/202009/26/20201.011/10/2020 Low white blood cell countUNKNaNKirkland Multivitamin, Kirkland Calcium vitamin, Vitamin D3, Fish OilNaNNaNNaNNaN201/01/2021NaNYNaNNaN
691660601/01/2021NV44.044.0NaNFNaNpatient called back the next day and stated her throat was swelling and had to take Benadryl.NaNNaNNaNNaNNaNNaNNaNNaNY12/29/202012/29/20200.0Did not seek medical care. Treated self at home with BenadrylPVTNaNNaNNaNNaNNaNNaN201/01/2021NaNNaNNaNiodine (shellfish) has epipen
791660701/01/2021KS50.050.0NaNMNaNSEVERE chills approximately 13-14 hours after receiving vaccine. Even after turning heat up in the house and wrapping myself in two comforters, I was still experiencing severe chills. These chills lasted for approximately 5-6 hours. I was unable to sleep due to them. I did not have a fever, as I checked my temperature several times during this episode. At approximately 6:00 am on the same day as experiencing the chills, I experienced abdominal pains, which lasted approximately 1 hour and resolved on their own.NaNNaNNaNNaNNaNNaNNaNNaNY12/28/202012/29/20201.0NonePUBNaNAmlodipine, Ambien, Benicar/HCTZ, Invokana, Metformin, Levothyroxine, Bydureon, MetoprololNoneHigh blood pressure, high cholesterol, sleep apnea, insomnia, diabetes type II, obesity.NaNNaN201/01/2021NaNNaNNaNPenicillin
891660801/01/2021OH33.033.0NaNMNaNNasal congestion and diarrheaNaNNaNNaNNaNNaNNaNNaNNaNNaN12/29/202012/31/20202.0NaNOTHNaNNoneNoneNoneNaNNaN201/01/2021NaNNaNNaNNone
991660901/01/2021TN71.071.0NaNFNaNOn day 9 following the vaccination I noticed a red raised itchy patch at the vaccination site approximately 2 in X 2 in. No other symptoms.NaNNaNNaNNaNNaNNaNNaNNaNN12/23/202012/31/20208.0NonePUBNaNMedication Summary 1/1/21 Name of Medication RX or OTC Doseage Frequency Reason Comment Meloxicam RX 15 mg 1 qd inflammation Synthroid RX 75 mcg. 1 qd, middle of night Thyroid hormone, T4 Liothyronine SOD RX 10 mcg 1 qd,noneHashimoto's thyroiditis, Hypertension, depressionNaNNaN201/01/2021NaNNaNNaNSulfa antibiotics, azithromycin, adhesive in band-aids or tape

Last rows

VAERS_IDRECVDATESTATEAGE_YRSCAGE_YRCAGE_MOSEXRPT_DATESYMPTOM_TEXTDIEDDATEDIEDL_THREATER_VISITHOSPITALHOSPDAYSX_STAYDISABLERECOVDVAX_DATEONSET_DATENUMDAYSLAB_DATAV_ADMINBYV_FUNDBYOTHER_MEDSCUR_ILLHISTORYPRIOR_VAXSPLTTYPEFORM_VERSTODAYS_DATEBIRTH_DEFECTOFC_VISITER_ED_VISITALLERGIES
569491170804309/17/2021GA25.025.0NaNFNaNVaccine had expired on 08/24/2021NaNNaNNaNNaNNaNNaNNaNNaNNaN08/26/202108/26/20210.0nonePUBNaNUNKNOWN.UNKNOWN.UNKNOWNNaNNaN209/17/2021NaNNaNNaNNKA.
569492170804409/17/2021NC30.030.0NaNFNaNDescription of events from Patient Message sent through our patient portal: "On August 15th I got the Pfizer vaccine. I have been on birth control for probably 4-5 years now and I?ve always had a little nausea if I forget it and then double up to make up for it but never anything weird or out of the ordinary has happened the entire time I?ve been on birth control. I missed two days of birth control, Friday and Saturday, I doubled up on Sunday (22nd) and Monday (23rd). I received my allergy immunology shot on Monday 23rd (I?m building up still, so I get them every Monday). My tongue swelled on Monday 23rd and got incredibly sore to the point where it was painful to speak. Internet said it could be hormonal.. so I called the pharmacy where I got my birth control ask if that can be a hormonal reaction involving birth control, they said no. I contacted my allergist since I received that the same day, before she was in the allergy department she was an OBGYN, and said that it?s more likely to be hormone related since, I had doubled up. Since the swelling started toward the evening, and not following immediately after the shot, she said it?s very likely to be hormone related. I have never had anything weird like that happen, and it was followed by an entire week of miserable nausea. Out of my female family and female friends who received a covid vaccine, most have had hormonal/heavy/clotted menstrual reactions to the covid vaccines. Since hormones effect menstrual cycles, and my tongue swelling was followed by an entire week of incredible nausea, I figured it might be helpful to report."NaNNaNNaNNaNNaNNaNNaNNaNY08/15/202108/23/20218.0NaNPVTNaNYaz , Zyrtec, FluticasoneNaNGADNaNNaN209/17/2021NaNNaNNaNPercocet
569493170804509/17/2021WI46.046.0NaNFNaNRandom period in the middle of birth control cycle But your system doesn?t even know it is JOHNSON & JOHNSON - NOT JANSSENNaNNaNNaNNaNNaNNaNNaNNaNU09/02/202109/15/202113.0NaNPHMNaNEstrylla (BCP) Methimazole ((2.5 mg 4x/week)NaNGraves DiseaseNaNNaN209/17/2021NaNNaNNaNPeas, fish
569494170804609/17/2021OR38.038.0NaNFNaNPatient reports large, wide-spread, pruritic hives about 10 minutes after the injection. She had no other symptoms. She self-treated with and old prescription for prednisone intermittently for about 12 days.NaNNaNNaNNaNNaNNaNNaNNaNY09/03/202109/03/20210.0None.PVTNaNDicyclomine; Cyclobenzaprine; Lisinopril; Albuterol; Ibuprofen.Recent COVID infection.Hypertension; Thrombocytosis; Mild intermittent asthma; Depression; Dyslipidemia; Migraine with aura; Chronic hives.NaNNaN209/17/2021NaNYNaNMedroxyprogesterone; Adhesive tape; Aripiprazole; Estradiol-testosterone; Latex; Lithium; Oxycodone; Transparent dressings; Quetiapine; Ziprasidone.
569495170804709/17/2021GA56.056.0NaNMNaNBasically: It seems relatively likely there is some neuropathy that may be piriformis/IT related but I cant assess it fully w the PE burden, weight, and his knee safety (and even if I could be cant do the stretches right now) but I would guess its neuropathy w some piriformis tightness worsening it. Then large burden PEs, many, days later, negative covid x2, up to date cancer screenings, no fhx PE/lupus/hypercoag/cancer. 56yo morbid obesity and R knee fx, presented here w SOB and found to have multiple large Pes. Story as follows: recieved second dose moderna 9/1, 9/2 he had tingling in his R knee w some swelling and joint pains more diffuse. He has baselie chronic R knee pain after accident at six flags w acl tear, meniscus tear, and fx after the boat ride accident in 2016 and he uses a L handed cane since. This progressed and by 9/3 there was R hip pain, and tingling, by 9/5 tingling in both LE b/l and weakness, the toes felt numb and the R hip pain was worse. He went to an ED and was palced on muscle relaxant steroid injection and po steroid, no benefit, came to our ed and had ct a few days after negative again steroid injection given. 2 days ago sob worsened and he had xray at medstop, sent home. Presented here elevated DD and significant PE burden. He has some LE swelling at baseline but this is more than usual and he is easy out of breath more than usual. Normal colonscopy 6 months ago anf no fhx of cancers or blood clots.NaNNaNYNaNYNaNNaNYN09/01/202109/02/20211.0CTA w large burden b/l PEsPVTNaNIbuprofenNaNMorbid obesity (52) Chronic R knee traumatic injury (2006) New onset DM2 (a1c 7.7, dx in hospital)NaNNaN209/17/2021NaNYYNone
569496170804809/17/2021ME33.033.0NaNFNaNNight of shot: Extreme fatigue, muscle aches left side of chest, back, and neck Day 2: Extreme fatigue, muscle aches, joint ache, headache, felt similar to a flu/hangover Day 3&4: Extreme fatigue, muscle aches, joint ache, headache, felt similar to a flu/hangover, ear ache, lymphnodepathy front neck lympthnodes. Hurt to put on deodorant left arm Day 5:Extreme fatigue, muscle aches, joint ache, severe headache, felt similar to a flu/hangover Day 6 &7: fatigue, headache, inner ear pain, increased mucosa production Day 8, 9, 10: increased mucosa production, sore throat resulting in cough and painful to ingest fluids or solids. Failed all exams during this period due to impaired cognitive abilities.NaNNaNNaNNaNNaNNaNNaNNaNN09/07/202109/07/20210.0Not everyone has health insurance or can afford health insurance.PHMNaNNaNNaNNaNNaNNaN209/17/2021NaNNaNNaNErythromycin, sulfa, penicillin
569497170804909/17/2021IL49.049.0NaNFNaNI started to break out in a rash about 2 hours after the shot. By morning, it covered a large portion of behind my arm, back of legs, and knees. I also had a racing pulse of over 110, severe headache, leg and foot cramping, loss of appetite, fever, a foggy feeling where I could not speak properly or keep my thoughts in line.NaNNaNNaNNaNNaNNaNNaNNaNN09/10/202109/10/20210.0There was no infection, no virus. Blood work came back normal. Only showed signs of dehydration.PHMNaNGlipizide, Metformin, Losartan, Atorvastatin, Sertraline, Gabapentin.None.Diabetic; Partial Thyroid Removal due to nodule.NaNNaN209/17/2021NaNYYDemerol; Pineapple; Seafood/Shellfish.
569498170805009/17/2021NYNaNNaNNaNUNaNCold sweats mostly at night sometimes during the day, body aches, joint pain, burning sensation in stomach mostly at night. Symptoms generally come in waves and are at times more tolerable than others.NaNNaNNaNNaNNaNNaNNaNNaNUNaNNaNNaNNaNPHMNaNNaNNaNNaNNaNNaN209/17/2021NaNNaNNaNNaN
569499170805209/17/2021ME42.042.0NaNFNaNMy husband had the shot and 2 days after I started my period again after it had just ended 3 days before his shot and it lasted for a full month. I also had night sweats, chills, body aches, tired all the time, as well as insomnia. This lasted for a full month. I tried to report to my doctor, but they were in denial that this could be vaccine shedding. A co-workers husband who also works at the SY and got the the J&J shot suffered the same affects as I did.NaNNaNNaNNaNNaNNaNNaNNaNY06/10/202106/12/20212.0None. Dr's office was in denial after I reported issues related to vaccine shedding.MILNaNflonase, claritin.noneadenomyosis, chronic sinusitis, arthritis, migrainesNaNNaN209/17/2021NaNNaNNaNNaN
569500170805309/17/2021FL68.068.0NaNMNaNMy right thumb now "SHAKES" when I use it and my index finger togetherNaNNaNNaNNaNNaNNaNNaNNaNN02/07/202103/18/202139.0Doctor advise me to report it.OTHNaNNoneAfibAfibNaNNaN209/17/2021NaNNaNNaNNone